| papers by Patrick van der Smagt | Cited by | Year |
|---|---|---|
| TechOps: Technical Documentation Templates for the AI Act L Lucaj, A Loosley, H Jonsson, U Gasser, P van der Smagt arXiv preprint arXiv:2508.08804, 2025 | 2025 | |
| Accelerating crash simulations with Finite Element Method Integrated Networks (FEMIN): Comparing two approaches to replace large portions of a FEM simulation S Thel, L Greve, M Karl, P van der Smagt Computer Methods in Applied Mechanics and Engineering 443, 118046, 2025 | 2025 | |
| FlowQ: Energy-Guided Flow Policies for Offline Reinforcement Learning M Alles, N Chen, P van der Smagt, B Cseke arXiv preprint arXiv:2505.14139, 2025 | 2025 | |
| Constrained latent action policies for model-based offline reinforcement learning M Alles, P Becker-Ehmck, P van der Smagt, M Karl Advances in Neural Information Processing Systems 37, 70381-70405, 2024 | 2024 | |
| Human short-latency reflexes show precise short-term gain adaptation after prior motion P Stratmann, A Schmidt, H Höppner, P van der Smagt, T Meindl, ... Journal of Neurophysiology 132 (6), 1680-1692, 2024 | 1 | 2024 |
| Explaining decision structures and data value for neural networks in crop yield prediction M von Bloh, B Seiler, P van der Smagt, S Asseng Environmental Research Letters 19 (12), 124087, 2024 | 2024 | |
| Guided Decoding for Robot On-line Motion Generation and Adaption N Chen, B Cseke, E Aljalbout, A Paraschos, M Alles, P Van der Smagt 2024 IEEE-RAS 23rd International Conference on Humanoid Robots (Humanoids …, 2024 | 2024 | |
| Assistive AI for Augmenting Human Decision-making NM Gyöngyössy, B Török, C Farkas, L Lucaj, A Menyhárd, ... arXiv preprint arXiv:2410.14353, 2024 | 2024 | |
| Assistive AI for Augmenting Human Decision-making N Máté Gyöngyössy, B Török, C Farkas, L Lucaj, A Menyhárd, ... arXiv e-prints, arXiv: 2410.14353, 2024 | 2024 | |
| Adapting Deep Variational Bayes Filter for Enhanced Confidence Estimation in Finite Element Method Integrated Networks (FEMIN) S Thel, L Greve, M Karl, P van der Smagt arXiv preprint arXiv:2409.17758, 2024 | 2024 | |
| Sequential model for predicting patient adherence in subcutaneous immunotherapy for allergic rhinitis Y Li, Y Xiong, W Fan, K Wang, Q Yu, L Si, P van der Smagt, J Tang, ... Frontiers in Pharmacology 15, 1371504, 2024 | 2 | 2024 |
| Limt: Language-informed multi-task visual world models E Aljalbout, N Sotirakis, P van der Smagt, M Karl, N Chen arXiv preprint arXiv:2407.13466, 2024 | 5 | 2024 |
| The Shortcomings of Force-from-Motion in Robot Learning E Aljalbout, F Frank, P van der Smagt, A Paraschos arXiv preprint arXiv:2407.02904, 2024 | 2024 | |
| Introducing finite element method integrated networks (FEMIN) S Thel, L Greve, B van de Weg, P van der Smagt Computer Methods in Applied Mechanics and Engineering 427, 117073, 2024 | 4 | 2024 |
| Pragmatic auditing: a pilot-driven approach for auditing Machine Learning systems D Benbouzid, C Plociennik, L Lucaj, M Maftei, I Merget, A Burchardt, ... arXiv preprint arXiv:2405.13191, 2024 | 1 | 2024 |
| Design and Implementation of a Robotic Testbench for Analyzing Pincer Grip Execution in Human Specimen Hands N Wilhelm, C Glowalla, S Haddadin, J Schote, H Höppner, ... 2024 IEEE International Conference on Robotics and Automation (ICRA), 18465 …, 2024 | 2024 | |
| Accurate Kinematic Modeling using Autoencoders on Differentiable Joints N Wilhelm, S Haddadin, R Burgkart, P Van Der Smagt, M Karl 2024 IEEE International Conference on Robotics and Automation (ICRA), 7122-7128, 2024 | 1 | 2024 |
| On the role of the action space in robot manipulation learning and sim-to-real transfer E Aljalbout, F Frank, M Karl, P van der Smagt IEEE Robotics and Automation Letters 9 (6), 5895-5902, 2024 | 31 | 2024 |
| A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation Y Li, Q Chen, K Wang, M Li, L Si, Y Guo, Y Xiong, Q Wang, Y Qin, L Xu, ... arXiv preprint arXiv:2404.03253, 2024 | 3 | 2024 |
| 1991T-Like Type Ia Supernovae as an Extension of the Normal Population JT O’Brien, WE Kerzendorf, A Fullard, R Pakmor, J Buchner, C Vogl, ... The Astrophysical Journal 964 (2), 137, 2024 | 6 | 2024 |
| Scalable stellar evolution forecasting K Maltsev, FRN Schneider, FK Roepke, AI Jordan, GA Qadir, ... ASTRONOMY & ASTROPHYSICS 681, 2024 | 2024 | |
| Exploring under constraints with model-based actor-critic and safety filters A Agha, B Kayalibay, A Mirchev, P van der Smagt, J Bayer 8th Annual Conference on Robot Learning, 2024 | 3 | 2024 |
| Overcoming Knowledge Barriers: Online Imitation Learning from Observation with Pretrained World Models X Zhang, P Becker-Ehmck, P van der Smagt, M Karl First Workshop on Controllable Video Generation@ ICML24, 2024 | 2024 | |
| Guided Decoding for Robot Motion Generation and Adaption N Chen, E Aljalbout, B Cseke, P van der Smagt CoRR, 2024 | 2024 | |
| Scalable stellar evolution forecasting-Deep learning emulation versus hierarchical nearest-neighbor interpolation K Maltsev, FRN Schneider, FK Röpke, AI Jordan, GA Qadir, ... Astronomy & Astrophysics 681, A86, 2024 | 6 | 2024 |
| Action inference by maximising evidence: zero-shot imitation from observation with world models X Zhang, P Becker-Ehmck, P van der Smagt, M Karl Advances in Neural Information Processing Systems 36, 46284-46303, 2023 | 7 | 2023 |
| A sector-based approach to AI ethics: Understanding ethical issues of AI-related incidents within their sectoral context D Burema, N Debowski-Weimann, A von Janowski, J Grabowski, M Maftei, ... Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 705-714, 2023 | 21 | 2023 |
| Ai regulation is (not) all you need L Lucaj, P Van Der Smagt, D Benbouzid Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023 | 50 | 2023 |
| Filter-Aware Model-Predictive Control B Kayalibay, A Mirchev, A Agha, P van der Smagt, J Bayer Learning for Dynamics and Control Conference, 1441-1454, 2023 | 2023 | |
| Clas: Coordinating multi-robot manipulation with central latent action spaces E Aljalbout, M Karl, P van der Smagt Learning for Dynamics and Control Conference, 1152-1166, 2023 | 6 | 2023 |
| PRISM: Probabilistic Real-Time Inference in Spatial World Models A Mirchev, B Kayalibay, A Agha, P van der Smagt, D Cremers, J Bayer Conference on Robot Learning, 161-174, 2023 | 2 | 2023 |
| Local distance preserving auto-encoders using continuous knn graphs N Chen, P van der Smagt, B Cseke Topological, Algebraic and Geometric Learning Workshops 2022, 55-66, 2022 | 4 | 2022 |
| Probabilistic Dalek--Emulator framework with probabilistic prediction for supernova tomography W Kerzendorf, N Chen, J O'Brien, J Buchner, P van der Smagt arXiv preprint arXiv:2209.09453, 2022 | 1 | 2022 |
| Local distance preserving auto-encoders using continuous k-nearest neighbours graphs N Chen, P van der Smagt, B Cseke arXiv preprint arXiv:2206.05909, 2022 | 1 | 2022 |
| Tracking and planning with spatial world models B Kayalibay, A Mirchev, P van der Smagt, J Bayer Learning for Dynamics and Control Conference, 124-137, 2022 | 2 | 2022 |
| New mass estimates for massive binary systems: a probabilistic approach using polarimetric radiative transfer AG Fullard, JT O’Brien, WE Kerzendorf, M Shrestha, JL Hoffman, R Ignace, ... The Astrophysical Journal 930 (1), 89, 2022 | 7 | 2022 |
| Flat Latent Manifolds for Human-machine Co-creation of Music N Chen, D Benbouzid, F Ferroni, M Nitschke, L Pinna, P van der Smagt arXiv preprint arXiv:2202.12243, 2022 | 1 | 2022 |
| Chronic Multi-Electrode Electromyography in Snakes GW Jensen, P van der Smagt, H Luksch, H Straka, T Kohl Frontiers in Behavioral Neuroscience 15, 761891, 2022 | 2022 | |
| Flat latent manifolds for music improvisation between human and machine N Chen, D Benbouzid, F Ferroni, M Nitschke, L Pinna, P van der Smagt CoRR, 2022 | 2022 | |
| Constrained probabilistic movement primitives for robot trajectory adaptation F Frank, A Paraschos, P van der Smagt, B Cseke IEEE Transactions on Robotics 38 (4), 2276-2294, 2021 | 54 | 2021 |
| Latent matters: Learning deep state-space models A Klushyn, R Kurle, M Soelch, B Cseke, P van der Smagt Advances in Neural Information Processing Systems 34, 10234-10245, 2021 | 49 | 2021 |
| An adaptive mechatronic exoskeleton for force-controlled finger rehabilitation T Dickmann, NJ Wilhelm, C Glowalla, S Haddadin, P van der Smagt, ... Frontiers in Robotics and AI 8, 716451, 2021 | 8 | 2021 |
| Probabilistic reconstruction of type Ia supernova SN 2002bo JT O’Brien, WE Kerzendorf, A Fullard, M Williamson, R Pakmor, J Buchner, ... The Astrophysical Journal Letters 916 (2), L14, 2021 | 7 | 2021 |
| Layerwise learning for quantum neural networks A Skolik, JR McClean, M Mohseni, P Van Der Smagt, M Leib Quantum Machine Intelligence 3 (1), 5, 2021 | 377 | 2021 |
| Dalek: a deep learning emulator for tardis WE Kerzendorf, C Vogl, J Buchner, G Contardo, M Williamson, ... The Astrophysical Journal Letters 910 (2), L23, 2021 | 24 | 2021 |
| Mind the gap when conditioning amortised inference in sequential latent-variable models J Bayer, M Soelch, A Mirchev, B Kayalibay, P van der Smagt arXiv preprint arXiv:2101.07046, 2021 | 20 | 2021 |
| Exploration via empowerment gain: Combining novelty, surprise and learning progress P Becker-Ehmck, M Karl, J Peters, P van der Smagt ICML 2021 Workshop on Unsupervised Reinforcement Learning, 2021 | 7 | 2021 |
| Less Suboptimal Learning and Control in Variational POMDPs B Kayalibay, A Mirchev, P van der Smagt, J Bayer Self-Supervision for Reinforcement Learning Workshop-ICLR, 2021 | 3 | 2021 |
| SnakeStrike: A Low-Cost Open-Source High-Speed Multi-Camera Motion Capture System GW Jensen, P Van der Smagt, E Heiss, H Straka, T Kohl Frontiers in Behavioral Neuroscience 14, 116, 2020 | 9 | 2020 |
| Estimating fingertip forces, torques, and local curvatures from fingernail images N Chen, G Westling, BB Edin, P van der Smagt Robotica 38 (7), 1242-1262, 2020 | 19 | 2020 |
| Variational state-space models for localisation and dense 3d mapping in 6 dof A Mirchev, B Kayalibay, P van der Smagt, J Bayer arXiv preprint arXiv:2006.10178, 2020 | 11 | 2020 |
| When Machine Learning Implies Intelligence [Young Professionals] P van der Smagt IEEE Robotics & Automation Magazine 27 (2), 19-19, 2020 | 2020 | |
| Learning to fly via deep model-based reinforcement learning P Becker-Ehmck, M Karl, J Peters, P van der Smagt arXiv preprint arXiv:2003.08876, 2020 | 55 | 2020 |
| Learning flat latent manifolds with vaes N Chen, A Klushyn, F Ferroni, J Bayer, P Van Der Smagt arXiv preprint arXiv:2002.04881, 2020 | 59 | 2020 |
| Beta dvbf: Learning state-space models for control from high dimensional observations N Das, M Karl, P Becker-Ehmck, P van der Smagt arXiv preprint arXiv:1911.00756, 2019 | 5 | 2019 |
| Variational tracking and prediction with generative disentangled state-space models A Akhundov, M Soelch, J Bayer, P van der Smagt arXiv preprint arXiv:1910.06205, 2019 | 6 | 2019 |
| Unsupervised real-time control through variational empowerment M Karl, P Becker-Ehmck, M Soelch, D Benbouzid, P van der Smagt, ... The International Symposium of Robotics Research, 158-173, 2019 | 65 | 2019 |
| Increasing the generalisaton capacity of conditional vaes A Klushyn, N Chen, B Cseke, J Bayer, P van der Smagt International Conference on Artificial Neural Networks, 779-791, 2019 | 2 | 2019 |
| On deep set learning and the choice of aggregations M Soelch, A Akhundov, P van der Smagt, J Bayer International Conference on Artificial Neural Networks, 444-457, 2019 | 29 | 2019 |
| Fast approximate geodesics for deep generative models N Chen, F Ferroni, A Klushyn, A Paraschos, J Bayer, P van der Smagt International Conference on Artificial Neural Networks, 554-566, 2019 | 29 | 2019 |
| Estimating Fingertip Forces, Torques, and Local Curvatures from Fingernail Images Nutan Chen†, Göran Westling‡, Benoni B. Edin‡ and P van der Smagt arXiv preprint arXiv:1909.05659, 2019 | 2019 | |
| Teaching a robot to see how it moves P van der Smagt Neural Network Perspectives on Cognition and Adaptive Robotics, 195-219, 2019 | 4 | 2019 |
| Multi-source neural variational inference R Kurle, S Günnemann, P Van der Smagt Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4114-4121, 2019 | 31 | 2019 |
| Early integration for movement modeling in latent spaces R Hornung, N Chen, P van der Smagt The Handbook of Multimodal-Multisensor Interfaces: Language Processing …, 2019 | 3* | 2019 |
| Switching linear dynamics for variational bayes filtering P Becker-Ehmck, J Peters, P Van Der Smagt International conference on machine learning, 553-562, 2019 | 66 | 2019 |
| Bayesian learning of neural network architectures G Dikov, J Bayer The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 46 | 2019 |
| ORC—a lightweight, lightning-fast middleware F Frank, A Paraschos, P van der Smagt 2019 Third IEEE International Conference on Robotic Computing (IRC), 337-343, 2019 | 5 | 2019 |
| Continual learning with bayesian neural networks for non-stationary data R Kurle, B Cseke, A Klushyn, P Van Der Smagt, S Günnemann International Conference on Learning Representations, 2019 | 105 | 2019 |
| Learning hierarchical priors in vaes A Klushyn, N Chen, R Kurle, B Cseke, P van der Smagt Advances in neural information processing systems 32, 2019 | 125 | 2019 |
| Active learning based on data uncertainty and model sensitivity N Chen, A Klushyn, A Paraschos, D Benbouzid, P Van der Smagt 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018 | 18 | 2018 |
| Approximate bayesian inference in spatial environments A Mirchev, B Kayalibay, M Soelch, P van der Smagt, J Bayer arXiv preprint arXiv:1805.07206, 2018 | 27 | 2018 |
| Metrics for deep generative models N Chen, A Klushyn, R Kurle, X Jiang, J Bayer, P Smagt International Conference on Artificial Intelligence and Statistics, 1540-1550, 2018 | 149 | 2018 |
| Gaussian process neurons S Urban, P van der Smagt | 1 | 2018 |
| Navigation and planning in latent maps B Kayalibay, A Mirchev, M Soelch, P Van Der Smagt, J Bayer FAIM workshop “Prediction and Generative Modeling in Reinforcement Learning 4, 2018 | 4 | 2018 |
| Gaussian process neurons learn stochastic activation functions S Urban, M Basalla, P van der Smagt arXiv preprint arXiv:1711.11059, 2017 | 8 | 2017 |
| Automatic differentiation for tensor algebras S Urban, P van der Smagt arXiv preprint arXiv:1711.01348, 2017 | 2 | 2017 |
| Two-stream RNN/CNN for action recognition in 3D videos R Zhao, H Ali, P Van der Smagt 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 144 | 2017 |
| Design and evaluation of a haptic interface with octopod kinematics M Kühne, J Potzy, R García-Rochín, P van der Smagt, A Peer IEEE/ASME Transactions on Mechatronics 22 (5), 2091-2101, 2017 | 9 | 2017 |
| SynEM, automated synapse detection for connectomics B Staffler, M Berning, KM Boergens, A Gour, P van der Smagt, ... Elife 6, e26414, 2017 | 73 | 2017 |
| Hitting the sweet spot: Automatic optimization of energy transfer during tool-held hits J Vogel, N Takemura, H Höppner, P van der Smagt, G Ganesh 2017 IEEE international conference on robotics and automation (ICRA), 1549-1556, 2017 | 4 | 2017 |
| Key insights into hand biomechanics: human grip stiffness can be decoupled from force by cocontraction and predicted from electromyography H Höppner, M Große-Dunker, G Stillfried, J Bayer, P Van Der Smagt Frontiers in neurorobotics 11, 17, 2017 | 27 | 2017 |
| Connecting artificial brains to robots in a comprehensive simulation framework: the neurorobotics platform E Falotico, L Vannucci, A Ambrosano, U Albanese, S Ulbrich, ... Frontiers in neurorobotics 11, 2, 2017 | 154 | 2017 |
| CNN-based segmentation of medical imaging data B Kayalibay, G Jensen, P Van Der Smagt arXiv preprint arXiv:1701.03056, 2017 | 683 | 2017 |
| Dynamic movement primitives in latent space of time-dependent variational autoencoders N Chen, M Karl, P Van Der Smagt 2016 IEEE-RAS 16th international conference on humanoid robots (Humanoids …, 2016 | 79 | 2016 |
| Boost online virtual network embedding: Using neural networks for admission control A Blenk, P Kalmbach, P Van Der Smagt, W Kellerer 2016 12th International Conference on Network and Service Management (CNSM …, 2016 | 66 | 2016 |
| Overview of the CPS for smart factories project: Deep learning, knowledge acquisition, anomaly detection and intelligent user interfaces D Sonntag, S Zillner, P van der Smagt, A Lörincz Industrial internet of things: Cybermanufacturing systems, 487-504, 2016 | 64 | 2016 |
| Stable reinforcement learning with autoencoders for tactile and visual data H Van Hoof, N Chen, M Karl, P Van Der Smagt, J Peters 2016 IEEE/RSJ international conference on intelligent robots and systems …, 2016 | 219 | 2016 |
| Variational inference with hamiltonian monte carlo C Wolf, M Karl, P van der Smagt arXiv preprint arXiv:1609.08203, 2016 | 49 | 2016 |
| Evaluation of joint type modelling in the human hand A Gustus, P van der Smagt Journal of Biomechanics 49 (13), 3097-3100, 2016 | 3 | 2016 |
| Learning Arbitrarily Complex Weight Uncertainties in Neural Networks S Sahm, E Cator, P van der Smagt | 2016 | |
| Musculoskeletal robots: scalability in neural control C Richter, S Jentzsch, R Hostettler, JA Garrido, E Ros, A Knoll, ... IEEE Robotics & Automation Magazine 23 (4), 128-137, 2016 | 72 | 2016 |
| Neurorobotics: From vision to action P Van Der Smagt, MA Arbib, G Metta Springer Handbook of Robotics, 2069-2094, 2016 | 20 | 2016 |
| Unsupervised preprocessing for tactile data M Karl, J Bayer, P van der Smagt arXiv preprint arXiv:1606.07312, 2016 | 4 | 2016 |
| ML-based tactile sensor calibration: A universal approach M Karl, A Lohrer, D Shah, F Diehl, M Fiedler, S Ognawala, J Bayer, ... arXiv preprint arXiv:1606.06588, 2016 | 2 | 2016 |
| Deep variational bayes filters: Unsupervised learning of state space models from raw data M Karl, M Soelch, J Bayer, P Van der Smagt arXiv preprint arXiv:1605.06432, 2016 | 488 | 2016 |
| A Differentiable Transition Between Additive and Multiplicative Neurons W Köpp, P van der Smagt, S Urban arXiv preprint arXiv:1604.03736, 2016 | 2 | 2016 |
| iEMG: Imaging electromyography H Urbanek, P van der Smagt Journal of Electromyography and Kinesiology 27, 1-9, 2016 | 38 | 2016 |
| Variational inference for on-line anomaly detection in high-dimensional time series M Sölch, J Bayer, M Ludersdorfer, P van der Smagt arXiv preprint arXiv:1602.07109, 2016 | 120 | 2016 |
| Scalability in neural control of musculoskeletal robots C Richter, S Jentzsch, R Hostettler, JA Garrido, E Ros, AC Knoll, ... arXiv preprint arXiv:1601.04862, 2016 | 17 | 2016 |
| Editorial Board of Biological Cybernetics: Advances in Computational Neuroscience JL van Hemmen, GB Ermentrout, W Senn, H Abarbanel, A Aertsen, ... Biol Cybern 110, 1-2, 2016 | 2016 | |
| Robust detection of anomalies via sparse methods ZÁ Milacski, M Ludersdorfer, A Lőrincz, P van der Smagt International Conference on Neural Information Processing, 419-426, 2015 | 18 | 2015 |
| Efficient movement representation by embedding dynamic movement primitives in deep autoencoders N Chen, J Bayer, S Urban, P Van Der Smagt 2015 IEEE-RAS 15th international conference on humanoid robots (Humanoids …, 2015 | 66 | 2015 |
| Efficient empowerment M Karl, J Bayer, P van der Smagt arXiv preprint arXiv:1509.08455, 2015 | 12 | 2015 |
| Two-dimensional orthoglide mechanism for revealing areflexive human arm mechanical properties H Höppner, M Grebenstein, P van der Smagt 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015 | 6 | 2015 |
| Measuring fingertip forces from camera images for random finger poses N Chen, S Urban, J Bayer, P van der Smagt 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015 | 10 | 2015 |
| Fast adaptive weight noise J Bayer, M Karl, D Korhammer, P van der Smagt arXiv preprint arXiv:1507.05331, 2015 | 5 | 2015 |
| Sensor calibration and hysteresis compensation with heteroscedastic gaussian processes S Urban, M Ludersdorfer, P Van Der Smagt IEEE Sensors Journal 15 (11), 6498-6506, 2015 | 30 | 2015 |
| An assistive decision-and-control architecture for force-sensitive hand–arm systems driven by human–machine interfaces J Vogel, S Haddadin, B Jarosiewicz, JD Simeral, D Bacher, LR Hochberg, ... The International Journal of Robotics Research 34 (6), 763-780, 2015 | 77 | 2015 |
| Flownet: Learning optical flow with convolutional networks P Fischer, A Dosovitskiy, E Ilg, P Häusser, C Hazırbaş, V Golkov, ... arXiv preprint arXiv:1504.06852, 2015 | 776 | 2015 |
| A neural transfer function for a smooth and differentiable transition between additive and multiplicative interactions S Urban, P van der Smagt arXiv preprint arXiv:1503.05724, 2015 | 11 | 2015 |
| Real-time Cerebellar Control of a Compliant Robotic Arm C Richter, S Jentzsch, F Röhrbein, P van der Smagt, J Conradt BCCN conference, Heidelberg, 2015 | 2015 | |
| Flownet: Learning optical flow with convolutional networks A Dosovitskiy, P Fischer, E Ilg, P Hausser, C Hazirbas, V Golkov, ... Proceedings of the IEEE International Conference on Computer Vision, 2758-2766, 2015 | 5034 | 2015 |
| Image super-resolution with fast approximate convolutional sparse coding C Osendorfer, H Soyer, P Van Der Smagt International Conference on Neural Information Processing, 250-257, 2014 | 96 | 2014 |
| Model-free robot anomaly detection R Hornung, H Urbanek, J Klodmann, C Osendorfer, P Van Der Smagt 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2014 | 60 | 2014 |
| A new biarticular joint mechanism to extend stiffness ranges H Hoppner, W Wiedmeyer, P van der Smagt 2014 IEEE International Conference on Robotics and Automation (ICRA), 2014 | 3 | 2014 |
| Estimating finger grip force from an image of the hand using convolutional neural networks and gaussian processes N Chen, S Urban, C Osendorfer, J Bayer, P Van Der Smagt 2014 IEEE International Conference on Robotics and Automation (ICRA), 3137-3142, 2014 | 20 | 2014 |
| A new biarticular joint mechanism to extend stiffness ranges H Höppner, W Wiedmeyer, P van der Smagt 2014 IEEE International Conference on Robotics and Automation (ICRA), 3403-3410, 2014 | 10 | 2014 |
| MRI-based skeletal hand movement model G Stillfried, U Hillenbrand, M Settles, P van der Smagt The human hand as an inspiration for robot hand development, 49-75, 2014 | 47 | 2014 |
| Continuous control of the dlr light-weight robot iii by a human with tetraplegia using the braingate2 neural interface system J Vogel, S Haddadin, JD Simeral, SD Stavisky, D Bacher, LR Hochberg, ... Experimental Robotics: The 12th International Symposium on Experimental …, 2014 | 44 | 2014 |
| Task dependency of grip stiffness—a study of human grip force and grip stiffness dependency during two different tasks with same grip forces H Höppner, J McIntyre, P van der Smagt PloS one 8 (12), e80889, 2013 | 21 | 2013 |
| On fast dropout and its applicability to recurrent networks J Bayer, C Osendorfer, D Korhammer, N Chen, S Urban, P van der Smagt arXiv preprint arXiv:1311.0701, 2013 | 97 | 2013 |
| Training neural networks with implicit variance J Bayer, C Osendorfer, S Urban, P van der Smagt International Conference on Neural Information Processing, 132-139, 2013 | 11 | 2013 |
| Continuous robot control using surface electromyography of atrophic muscles J Vogel, J Bayer, P Van Der Smagt 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013 | 44 | 2013 |
| Computing grip force and torque from finger nail images using gaussian processes S Urban, J Bayer, C Osendorfer, G Westling, BB Edin, P Van Der Smagt 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013 | 22 | 2013 |
| Convolutional neural networks learn compact local image descriptors C Osendorfer, J Bayer, S Urban, P van der Smagt International Conference on Neural Information Processing, 624-630, 2013 | 31 | 2013 |
| Robots driven by compliant actuators: Optimal control under actuation constraints DJ Braun, F Petit, F Huber, S Haddadin, P Van Der Smagt, ... IEEE transactions on robotics 29 (5), 1085-1101, 2013 | 195 | 2013 |
| Part II: ISER Session Summary on “Dynamics and Control” P van der Smagt Experimental Robotics: The 13th International Symposium on Experimental …, 2013 | 2013 | |
| Identification of human limb stiffness in 5 DoF and estimation via EMG D Lakatos, D Rüschen, J Bayer, J Vogel, P van der Smagt Experimental Robotics: The 13th International Symposium on Experimental …, 2013 | 11 | 2013 |
| Minimizing data consumption with sequential online feature selection T Rückstieß, C Osendorfer, P van der Smagt International Journal of Machine Learning and Cybernetics 4 (3), 235-243, 2013 | 25 | 2013 |
| Convolutional Neural Networks learn compact local image C Osendorfer, J Bayer, P van der Smagt arXiv preprint arXiv:1304.7948, 2013 | 2013 | |
| Evidence of muscle synergies during human grasping C Castellini, P van der Smagt Biological cybernetics 107 (2), 233-245, 2013 | 81 | 2013 |
| Relation between object properties and EMG during reaching to grasp N Fligge, H Urbanek, P van der Smagt Journal of Electromyography and Kinesiology 23 (2), 402-410, 2013 | 39 | 2013 |
| Unsupervised feature learning for low-level local image descriptors C Osendorfer, J Bayer, S Urban, P van der Smagt arXiv preprint arXiv:1301.2840, 2013 | 7 | 2013 |
| Foreword for the special issue on Multimodal and Sensorimotor Bionics JL van Hemmen, P van der Smagt, BE Stein Biological cybernetics 106 (11-12), 615, 2012 | 2 | 2012 |
| Human hand modelling: kinematics, dynamics, applications A Gustus, G Stillfried, J Visser, H Jörntell, P van der Smagt Biological cybernetics 106 (11), 741-755, 2012 | 147 | 2012 |
| Optimal torque and stiffness control in compliantly actuated robots DJ Braun, F Petit, F Huber, S Haddadin, P Van Der Smagt, ... 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2012 | 21 | 2012 |
| Learning sequence neighbourhood metrics J Bayer, C Osendorfer, P van der Smagt International Conference on Artificial Neural Networks, 531-538, 2012 | 13 | 2012 |
| Generating marker stars for 6D optical tracking D Gierlach, A Gustus, P van der Smagt 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and …, 2012 | 11 | 2012 |
| Patient performance evaluation using Kinect and Monte Carlo-based finger tracking F Cordella, F Di Corato, L Zollo, B Siciliano, P van der Smagt 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and …, 2012 | 50 | 2012 |
| Minimum jerk for human catching movements in 3D N Fligge, J McIntyre, P van der Smagt 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and …, 2012 | 33 | 2012 |
| Building the Ninapro database: A resource for the biorobotics community M Atzori, A Gijsberts, S Heynen, AGM Hager, O Deriaz, P Van Der Smagt, ... 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and …, 2012 | 346 | 2012 |
| Reach and grasp by people with tetraplegia using a neurally controlled robotic arm LR Hochberg, D Bacher, B Jarosiewicz, NY Masse, JD Simeral, J Vogel, ... Nature 485 (7398), 372-375, 2012 | 3156 | 2012 |
| 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) M Atzori, A Gijsberts, S Heynen, AGM Hager, O Deriaz, P Van Der Smagt, ... IEEE, 2012 | 55 | 2012 |
| Minimizing Data Consumption in Sequential Classification T Rückstiess, C Osendorfer, P Smagt International Journal of Machine Learning and Cybernetics, 2012 | 2012 | |
| Sequential feature selection for classification T Rückstieß, C Osendorfer, P Van Der Smagt Australasian joint conference on artificial intelligence, 132-141, 2011 | 143 | 2011 |
| Conditioning vs. excitation time for estimating impedance parameters of the human arm D Lakatos, F Petit, P Van Der Smagt 2011 11th IEEE-RAS International Conference on Humanoid Robots, 636-642, 2011 | 16 | 2011 |
| EMG-based teleoperation and manipulation with the DLR LWR-III J Vogel, C Castellini, P van der Smagt 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2011 | 153 | 2011 |
| Neue Entwicklungen in der Rehabilitation von Handfunktionsstörungen P van der Smagt Handfunktionsstörungen in der Neurologie: Klinik und Rehabilitation, 433, 2011 | 2011 | |
| Preliminary evidence of dynamic muscular synergies in human grasping C Castellini, P van der Smagt 2011 15th international conference on advanced robotics (ICAR), 28-33, 2011 | 7 | 2011 |
| The Grasp Perturbator: Calibrating human grasp stiffness during a graded force task H Höppner, D Lakatos, H Urbanek, C Castellini, P van der Smagt 2011 IEEE International Conference on Robotics and Automation, 3312-3316, 2011 | 22 | 2011 |
| Handfunktionsstörungen in der Neurologie: Klinik und Rehabilitation P van der Smagt Neue Entwicklungen in der Rehabilitation von Handfunktionsstörungen …, 2011 | 2011 | |
| Neue Entwicklungen in der Rehabilitation von Handfunktionsstörungen: Humanrobotik P Smagt Handfunktionsstörungen in der Neurologie: Klinik und Rehabilitation, 2011 | 2011 | |
| Bionik: Bionische Roboter (VDI 6222) J Albiez, C Ament, I Boblan, N Elkmann, P Ferrara, M Fischer, J Mämpel, ... | 2011 | |
| Unsupervised learning of low-level audio features for music similarity estimation C Osendorfer, J Schlüter, J Schmidhuber, P Smagt Workshop on Learning Architectures, Representations, and Optimization for …, 2011 | 10 | 2011 |
| STIFF: Enhancing biomorphic agility through variable stiffness P Van Der Smagt, F Van Der Helm, J Schmidhuber, S Vijayakumar, ... 4th International Conference on Cognitive Systems, CogSys 2010, 2010 | 2010 | |
| The DLR touch sensor I: A flexible tactile sensor for robotic hands based on a crossed-wire approach MW Strohmayr, HP Saal, AH Potdar, P van der Smagt 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2010 | 31 | 2010 |
| Movement model of a human hand based on magnetic resonance imaging (MRI) G Stillfried, P van der Smagt | 58 | 2010 |
| Control of a robotic arm using intracortical motor signal by an individual with tetraplegia in the BrainGate2 trial J Liu, JD Simeral, SD Stavisky, D Bacher, J Vogel, S Haddadin, P Smagt, ... 40th Annual Meeting in Neuroscience (SFN2010), 2010 | 1 | 2010 |
| The arm-perturbator: design of a wearable perturbation device to measure limb impedance H Höppner, D Lakatos, H Urbanek, P Smagt International Conference on Applied Bionics and Biomechanics (ICABB), 2010 | 1 | 2010 |
| Human arm impedance and EMG in 3D P van der Smagt, C Castellini, H Urbanek Enaction on SKILLS 15 (21), 191, 2009 | 1* | 2009 |
| Anticipatory grip force control using a cerebellar model JR De Gruijl, P van der Smagt, CI De Zeeuw Neuroscience 162 (3), 777-786, 2009 | 23 | 2009 |
| Robotics of human movements P van der Smagt, M Grebenstein, H Urbanek, N Fligge, M Strohmayr, ... Journal of Physiology-Paris 103 (3-5), 119-132, 2009 | 59 | 2009 |
| VIACTORS-Variable Impedance ACTuation systems embodying advanced interaction behaviors A Albu-Schaeffer, A Bicchi, S Stramigioli, E Burdet, P Smagt, A Parravicini, ... European Future Technologies Conference, FET09, 2009 | 6 | 2009 |
| Human hand kinematics based on MRI imaging G Stillfried, P van der Smagt Understanding the Human Hand for Advancing Robotic Manipulation Workshop at …, 2009 | 2 | 2009 |
| Surface EMG in advanced hand prosthetics C Castellini, P Van Der Smagt Biological cybernetics 100 (1), 35-47, 2009 | 567 | 2009 |
| Human-like robot hand. P van der Smagt Advanced Manufacturing Technology 29 (9), 10-11, 2008 | 2008 | |
| Surface EMG for force control of mechanical hands C Castellini, P Van Der Smagt, G Sandini, G Hirzinger 2008 IEEE International Conference on Robotics and Automation, 725-730, 2008 | 77 | 2008 |
| Neurorobotics: From vision to action MA Arbib, G Metta, P van der Smagt Springer handbook of robotics, 1453-1480, 2008 | 56 | 2008 |
| Calculation of Human Arm Stiffness Using a Biomechanical Model P Artati, P Van der Smagt, DIN Krüger, JMB Baena Ph. D. Thesis, 2008 | 1 | 2008 |
| Using MRI data to compute a hand kinematic model P van der Smagt, G Stillfried 9th conference on motion and vibration control (MOVIC), München, Germany, 2008 | 7* | 2008 |
| Human motion range data optimizes anthropomorphic robotic hand-arm system design H Panzer, O Eiberger, M Grebenstein, S Wolf, P Schaefer, P Smagt Proc. 9th International Conference on Motion and Vibration Control (MOVIC), 2008 | 4 | 2008 |
| Surface EMG suffices to classify the motion of each finger independently S Maier, P Smagt Proceedings of MOVIC. 9th International Conference on Motion and Vibration …, 2008 | 52 | 2008 |
| Antagonism for a highly anthropomorphic hand–arm system M Grebenstein, P Van der Smagt Advanced Robotics 22 (1), 39-55, 2008 | 124 | 2008 |
| Learning EMG control of a robotic hand: towards active prostheses S Bitzer, P Van Der Smagt Proceedings 2006 IEEE International Conference on Robotics and Automation …, 2006 | 336 | 2006 |
| NEUROBOTICS: The fusion of neuroscience and robotics P van der Smagt, G Hirzinger VDI BERICHTE 1956, 223, 2006 | 2006 | |
| Learning from demonstration: repetitive movements for autonomous service robotics H Urbanek, A Albu-Schaffer, P van der Smagt 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2004 | 47 | 2004 |
| Guest Editorial for Special Issue on Scalable Applications of Neural Networks to Robotics P van der Smagt, D Bullock Applied Intelligence 17 (1), 7-10, 2002 | 2002 | |
| Searching a scalable approach to cerebellar based control J Peters, P van der Smagt Applied intelligence 17 (1), 11-33, 2002 | 15 | 2002 |
| Solving the ill-conditioning in neural network learning P Van Der Smagt, G Hirzinger Neural networks: tricks of the trade, 193-206, 2002 | 45* | 2002 |
| Benchmarking cerebellar control P van der Smagt Robotics and Autonomous Systems 32 (4), 237-251, 2000 | 38 | 2000 |
| The cerebellum as computed torque model P van der Smagt, G Hirzinger KES'2000. Fourth International Conference on Knowledge-Based Intelligent …, 2000 | 14 | 2000 |
| An overview of cerebellar control P van der Smagt IEE Workshop on Self-Learning Robots III Brainstyle Robotics: The Cerebellum …, 1999 | 1999 | |
| Neuronale Perzeption und Manipulation multisensorieller Manipulatoren und Roboterhände R Koeppe, P Smagt, AO Albu-Schäffer, K Arbter, M Fischer, F Lange, ... | 1 | 1999 |
| Perception and manipulation in robotics- Neural network approaches R Koeppe, P van der Smagt, A Albu-Schaeffer, K Arbter, M Fischer, ... Cologne, Germany: Deutsches Zentrum fuer Luft- und Raumfahrt(DLR-Mitteilung …, 1999 | 1999 | |
| Why feed-forward networks are in a bad shape P van der Smagt, G Hirzinger International Conference on Artificial Neural Networks, 159-164, 1998 | 6 | 1998 |
| Cerebellar control of robot arms P van der Smagt Connection Science 10 (3-4), 301-320, 1998 | 36 | 1998 |
| Learning techniques in a dataglove based telemanipulation system for the DLR hand M Fischer, P Van Der Smagt, G Hirzinger Proceedings. 1998 IEEE International Conference on Robotics and Automation …, 1998 | 167 | 1998 |
| German Aerospace Research Establishment, Institute of Robotics and System Dynamics, PO Box 1116, D-82230 Wessling, Germany, smagt@ dlr. de http://www. robotic. dlr. de/Smagt P van der Smagt, G Hirzinger Neural Networks: Tricks of the Trade 1524, 193, 1998 | 1998 | |
| Book Review-//Neural systems for robotics M Zeller, O Omidvar, P Smagt Neural Networks 11 (6), 1141-1142, 1998 | 1998 | |
| Dynamic control in new robot structures: Can we learn nonlinear functions of high dimensionality? P van der Smagt Can Artificial erebellar Models ompete to, 5, 1997 | 1997 | |
| Neural networks and pattern recognition O Omidvar, J Dayhoff Elsevier, 1997 | 94 | 1997 |
| Neural systems for robotics O Omidvar, P van der Smagt Academic Press, 1997 | 69 | 1997 |
| Neural Systems for Robotics D DeMers, K Kreutz-Delgado, O Omidvar, P van der Smagt San Diego: Academic Press, 1997 | 5 | 1997 |
| Can artificial cerebellar models compete to control robots P van del Smagt, D Bullock Extended abstracts of the NIPS 97, 1997 | 10* | 1997 |
| Visual feedback in motion P van der Smagt, F Groen Neural systems for robotics, 37-73, 1997 | 5 | 1997 |
| Analysis and control of a Rubbertuator arm F Groen, P van der Smagt, K Schulten Biological Cybernetics 75 (5), 433-440, 1996 | 7 | 1996 |
| Analysis and control of a rubbertuator arm P van der Smagt, F Groen, K Schulten Biological Cybernetics 75 (5), 433-440, 1996 | 111 | 1996 |
| A robot arm is neurally controlled using monocular feedback P Van Der Smagt IEE Colloquium on Self Learning Robots, 9/1-9/3, 1996 | 1996 | |
| An introduction to neural networks B Kröse, P van der Smagt | 1566 | 1996 |
| Approximation with neural networks: Between local and global approximation P van der Smagt, F Groen Proceedings of ICNN'95-International Conference on Neural Networks 2, 1060-1064, 1995 | 18 | 1995 |
| Computer Systemen en Applicaties P van der Smagt | 1995 | |
| A monocular robot arm can be neurally positioned P van Der Smagt, FCA Groen, BJA Kröse 1995, International Conference on Intelligent Autonomous Systems, 1995 | 3 | 1995 |
| Visual robot arm guidance using neural networks P van der Smagt | 32 | 1995 |
| U. Rembold et al.(Eds.) P van der Smagt, FCA Groen, BJA Kröse Intelligent Autonomous Systems: IAS-4: Proceedings of the International …, 1995 | 1995 | |
| A Visually Guided Robot and a Neural Network Join to Grasp Slanted Objects FCA Groen, PPP van der Smagt, A Dev Springer Verlag, 1995 | 1995 | |
| A Pilot Study Into Parallel Hierarchical SOM's P van der Smagt, FCA Groen, LO Hertzberger Universiteit van Amsterdam. Department of Computer Systems, 1995 | 1995 | |
| Using many-particle decomposition to get a parallel self-organising map PPP van der Smagt, BJA Kröse SION, 1995 | 1 | 1995 |
| Nested networks for robot control A Jansen, P van der Smagt, F Groen Applications of neural networks, 221-239, 1995 | 15 | 1995 |
| A visually guided robot and a neural network join to grasp slanted objects P van der Smagt, A Dev, FCA Groen Neural Networks: Artificial Intelligence and Industrial Applications …, 1995 | 1995 | |
| Miss v P van der Smagt, FCA Groen, BJA Krose | 1994 | |
| The locally linear nested network for robot manipulation P van der Smagt, F Groen, F van het Groenewoud Neural Networks, 1994. IEEE World Congress on Computational Intelligence …, 1994 | 15 | 1994 |
| Simderella: A robot simulator for neuro-controller design P van der Smagt Neurocomputing 6 (2), 281-285, 1994 | 35 | 1994 |
| Neural network control of a pneumatic robot arm T Hesselroth, K Sarkar, P van der Smagt, K Schulten Systems, Man and Cybernetics, IEEE Transactions on 24 (1), 28-38, 1994 | 237 | 1994 |
| Minimisation methods for training feed-forward networks P van der Smagt Neural Networks 7, 1-11, 1994 | 345 | 1994 |
| Robotic hand-eye coordination using multi-resolution linear perceptron representation P van der Smagt, F van het Groenewoud, F Groen | 1993 | |
| Faculty of Mathematics and Computer Science Biophysics Research Institute PP van der Smagt, MGP Bartholomeus ICANN’93: Proceedings of the International Conference on Artificial Neural …, 1993 | 1993 | |
| Neural Networks for Robot Eye-Hand Coordination FCA Groen, BJA Kröse, PP van der Smagt, MGP Bartholomeus, AJ Noest International Conference on Artificial Neural Networks, 211-218, 1993 | 1993 | |
| Robot hand-eye coordination using neural networks P van der Smagt, F Groen, B Kröse Universiteit van Amsterdam. Department of Computer Systems, 1993 | 11 | 1993 |
| Control of pneumatic robot arm dynamics by a neural network P Van der Smagt, K Schulten Proc. of the 1993 World Congress on Neural Networks 3, 180-183, 1993 | 17 | 1993 |
| An introduction to neural networks. 1993 B Kröse, B Krose, P van der Smagt, P Smagt Doi: http://citeseerx. ist. psu. edu/viewdoc/summary, 1993 | 34* | 1993 |
| A one-eyed self learning robot manipulator BJA Kröse, PP van der Smagt, FCA Groen Neural Networks in Robotics, 19-28, 1993 | 7 | 1993 |
| Interpolative robot control with the nested network approach P van der Smagt, A Jansen, FCA Groen Proceedings of the 1992 IEEE International Symposium on Intelligent Control …, 1992 | 8 | 1992 |
| High-precision robot control: The nested network A Jansen, P van der Smagt, F Groen Artificial Neural Networks 2, 583-586, 1992 | 2 | 1992 |
| A Self-learning Controller For Monocular Grasping. PP van der Smagt, BJA Kröse, FCA Groen IROS, 177-181, 1992 | 12 | 1992 |
| A real-time learning neural robot controller P van der Smagt, J Krose Proceedings of the 1991 International Conference on Artificial Neural …, 1991 | 67 | 1991 |
| A comparative study of neural network algorithms applied to optical character recognition P van der Smagt Proceedings of the 3rd international conference on Industrial and …, 1990 | 28 | 1990 |