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Patrick van der Smagt
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- affiliation: German Aerospace Center, Germany
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2020 – today
- 2024
- [j24]Elie Aljalbout
, Felix Frank
, Maximilian Karl
, Patrick van der Smagt
:
On the Role of the Action Space in Robot Manipulation Learning and Sim-to-Real Transfer. IEEE Robotics Autom. Lett. 9(6): 5895-5902 (2024) - [c66]Nikolas J. Wilhelm, Sami Haddadin, Rainer Burgkart, Patrick van der Smagt, Maximilian Karl:
Accurate Kinematic Modeling using Autoencoders on Differentiable Joints. ICRA 2024: 7122-7128 - [c65]Nikolas J. Wilhelm, Claudio Glowalla, Sami Haddadin, Julian Schote, Hannes Höppner, Patrick van der Smagt, Maximilian Karl, Rainer Burgkart:
Design and Implementation of a Robotic Testbench for Analyzing Pincer Grip Execution in Human Specimen Hands. ICRA 2024: 18465-18471 - [i52]Yin Li, Yu Xiong, Wenxin Fan, Kai Wang, Qingqing Yu, Liping Si, Patrick van der Smagt
, Jun Tang, Nutan Chen:
Sequential Model for Predicting Patient Adherence in Subcutaneous Immunotherapy for Allergic Rhinitis. CoRR abs/2401.11447 (2024) - [i51]Nutan Chen, Elie Aljalbout, Botond Cseke, Patrick van der Smagt
:
Guided Decoding for Robot Motion Generation and Adaption. CoRR abs/2403.15239 (2024) - [i50]Yin Li, Qi Chen, Kai Wang, Meige Li, Liping Si, Yingwei Guo, Yu Xiong, Qixing Wang, Yang Qin, Ling Xu, Patrick van der Smagt, Jun Tang, Nutan Chen:
A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation. CoRR abs/2404.03253 (2024) - [i49]Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl:
Overcoming Knowledge Barriers: Online Imitation Learning from Observation with Pretrained World Models. CoRR abs/2404.18896 (2024) - [i48]Djalel Benbouzid, Christiane Plociennik, Laura Lucaj, Mihai Maftei
, Iris Merget, Aljoscha Burchardt, Marc P. Hauer, Abdeldjallil Naceri, Patrick van der Smagt:
Pragmatic auditing: a pilot-driven approach for auditing Machine Learning systems. CoRR abs/2405.13191 (2024) - [i47]Elie Aljalbout, Felix Frank, Patrick van der Smagt, Alexandros Paraschos:
The Shortcomings of Force-from-Motion in Robot Learning. CoRR abs/2407.02904 (2024) - [i46]Elie Aljalbout, Nikolaos Sotirakis, Patrick van der Smagt, Maximilian Karl, Nutan Chen:
LIMT: Language-Informed Multi-Task Visual World Models. CoRR abs/2407.13466 (2024) - 2023
- [c64]Dafna Burema
, Nicole Debowski-Weimann
, Alexander von Janowski
, Jil Grabowski
, Mihai Maftei
, Mattis Jacobs
, Patrick van der Smagt
, Djalel Benbouzid
:
A sector-based approach to AI ethics: Understanding ethical issues of AI-related incidents within their sectoral context. AIES 2023: 705-714 - [c63]Laura Lucaj
, Patrick van der Smagt
, Djalel Benbouzid
:
AI Regulation Is (not) All You Need. FAccT 2023: 1267-1279 - [c62]Elie Aljalbout, Maximilian Karl, Patrick van der Smagt:
CLAS: Coordinating Multi-Robot Manipulation with Central Latent Action Spaces. L4DC 2023: 1152-1166 - [c61]Baris Kayalibay, Atanas Mirchev, Ahmed Agha, Patrick van der Smagt, Justin Bayer:
Filter-Aware Model-Predictive Control. L4DC 2023: 1441-1454 - [c60]Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl:
Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models. NeurIPS 2023 - [i45]Baris Kayalibay, Atanas Mirchev, Ahmed Agha, Patrick van der Smagt
, Justin Bayer:
Filter-Aware Model-Predictive Control. CoRR abs/2304.10246 (2023) - [i44]Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt
, Maximilian Karl:
Action Inference by Maximising Evidence: Zero-Shot Imitation from Observation with World Models. CoRR abs/2312.02019 (2023) - [i43]Elie Aljalbout, Felix Frank, Maximilian Karl, Patrick van der Smagt
:
On the Role of the Action Space in Robot Manipulation Learning and Sim-to-Real Transfer. CoRR abs/2312.03673 (2023) - 2022
- [j23]Felix Frank
, Alexandros Paraschos
, Patrick van der Smagt
, Botond Cseke:
Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation. IEEE Trans. Robotics 38(4): 2276-2294 (2022) - [c59]Atanas Mirchev, Baris Kayalibay, Ahmed Agha, Patrick van der Smagt, Daniel Cremers, Justin Bayer:
PRISM: Probabilistic Real-Time Inference in Spatial World Models. CoRL 2022: 161-174 - [c58]Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer:
Tracking and Planning with Spatial World Models. L4DC 2022: 124-137 - [c57]Nutan Chen, Patrick van der Smagt, Botond Cseke:
Local Distance Preserving Auto-encoders using Continuous kNN Graphs. TAG-ML 2022: 55-66 - [i42]Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer:
Tracking and Planning with Spatial World Models. CoRR abs/2201.10335 (2022) - [i41]Nutan Chen, Djalel Benbouzid, Francesco Ferroni, Mathis Nitschke, Luciano Pinna, Patrick van der Smagt:
Flat latent manifolds for music improvisation between human and machine. CoRR abs/2202.12243 (2022) - [i40]Nutan Chen, Patrick van der Smagt
, Botond Cseke:
Local distance preserving auto-encoders using Continuous k-Nearest Neighbours graphs. CoRR abs/2206.05909 (2022) - [i39]Wolfgang E. Kerzendorf, Nutan Chen, Jack O'Brien
, Johannes Buchner
, Patrick van der Smagt
:
Probabilistic Dalek - Emulator framework with probabilistic prediction for supernova tomography. CoRR abs/2209.09453 (2022) - [i38]Elie Aljalbout, Maximilian Karl, Patrick van der Smagt
:
CLAS: Coordinating Multi-Robot Manipulation with Central Latent Action Spaces. CoRR abs/2211.15824 (2022) - [i37]Atanas Mirchev, Baris Kayalibay, Ahmed Agha, Patrick van der Smagt
, Daniel Cremers
, Justin Bayer:
PRISM: Probabilistic Real-Time Inference in Spatial World Models. CoRR abs/2212.02988 (2022) - 2021
- [j22]Thomas Dickmann, Nikolas J. Wilhelm
, Claudio Glowalla, Sami Haddadin
, Patrick van der Smagt
, Rainer Burgkart:
An Adaptive Mechatronic Exoskeleton for Force-Controlled Finger Rehabilitation. Frontiers Robotics AI 8: 716451 (2021) - [j21]Andrea Skolik
, Jarrod R. McClean, Masoud Mohseni, Patrick van der Smagt
, Martin Leib:
Layerwise learning for quantum neural networks. Quantum Mach. Intell. 3(1): 1-11 (2021) - [c56]Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
:
Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models. ICLR 2021 - [c55]Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
, Justin Bayer:
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF. ICLR 2021 - [c54]Alexej Klushyn, Richard Kurle, Maximilian Soelch, Botond Cseke, Patrick van der Smagt:
Latent Matters: Learning Deep State-Space Models. NeurIPS 2021: 10234-10245 - [i36]Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt:
Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models. CoRR abs/2101.07046 (2021) - [i35]Felix Frank, Alexandros Paraschos, Patrick van der Smagt, Botond Cseke:
Constrained Probabilistic Movement Primitives for Robot Trajectory Adaptation. CoRR abs/2101.12561 (2021) - 2020
- [j20]Patrick van der Smagt
:
When Machine Learning Implies Intelligence [Young Professionals]. IEEE Robotics Autom. Mag. 27(2): 19 (2020) - [j19]Nutan Chen
, Göran Westling, Benoni B. Edin, Patrick van der Smagt
:
Estimating Fingertip Forces, Torques, and Local Curvatures from Fingernail Images. Robotica 38(7): 1242-1262 (2020) - [c53]Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick van der Smagt
, Stephan Günnemann:
Continual Learning with Bayesian Neural Networks for Non-Stationary Data. ICLR 2020 - [c52]Nutan Chen, Alexej Klushyn, Francesco Ferroni, Justin Bayer, Patrick van der Smagt:
Learning Flat Latent Manifolds with VAEs. ICML 2020: 1587-1596 - [i34]Nutan Chen, Alexej Klushyn, Francesco Ferroni, Justin Bayer, Patrick van der Smagt
:
Learning Flat Latent Manifolds with VAEs. CoRR abs/2002.04881 (2020) - [i33]Philip Becker-Ehmck, Maximilian Karl
, Jan Peters, Patrick van der Smagt
:
Learning to Fly via Deep Model-Based Reinforcement Learning. CoRR abs/2003.08876 (2020) - [i32]Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
, Justin Bayer:
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF. CoRR abs/2006.10178 (2020) - [i31]Andrea Skolik, Jarrod R. McClean, Masoud Mohseni, Patrick van der Smagt, Martin Leib:
Layerwise learning for quantum neural networks. CoRR abs/2006.14904 (2020) - [i30]Wolfgang E. Kerzendorf
, Christian Vogl
, Johannes Buchner
, Gabriella Contardo, Marc Williamson, Patrick van der Smagt:
Dalek - a deep-learning emulator for TARDIS. CoRR abs/2007.01868 (2020)
2010 – 2019
- 2019
- [c51]Richard Kurle, Stephan Günnemann, Patrick van der Smagt
:
Multi-Source Neural Variational Inference. AAAI 2019: 4114-4121 - [c50]Maximilian Soelch, Adnan Akhundov, Patrick van der Smagt
, Justin Bayer:
On Deep Set Learning and the Choice of Aggregations. ICANN (1) 2019: 444-457 - [c49]Nutan Chen, Francesco Ferroni, Alexej Klushyn, Alexandros Paraschos, Justin Bayer, Patrick van der Smagt
:
Fast Approximate Geodesics for Deep Generative Models. ICANN (2) 2019: 554-566 - [c48]Alexej Klushyn, Nutan Chen, Botond Cseke, Justin Bayer, Patrick van der Smagt
:
Increasing the Generalisaton Capacity of Conditional VAEs. ICANN (2) 2019: 779-791 - [c47]Philip Becker-Ehmck, Jan Peters, Patrick van der Smagt
:
Switching Linear Dynamics for Variational Bayes Filtering. ICML 2019: 553-562 - [c46]Felix Frank
, Alexandros Paraschos, Patrick van der Smagt
:
ORC - A Lightweight, Lightning-Fast Middleware. IRC 2019: 337-343 - [c45]Maximilian Karl, Philip Becker-Ehmck, Maximilian Soelch, Djalel Benbouzid, Patrick van der Smagt
, Justin Bayer:
Unsupervised Real-Time Control Through Variational Empowerment. ISRR 2019: 158-173 - [c44]Alexej Klushyn, Nutan Chen, Richard Kurle, Botond Cseke, Patrick van der Smagt:
Learning Hierarchical Priors in VAEs. NeurIPS 2019: 2866-2875 - [c43]Atanas Mirchev, Baris Kayalibay, Maximilian Soelch, Patrick van der Smagt
, Justin Bayer:
Approximate Bayesian Inference in Spatial Environments. Robotics: Science and Systems 2019 - [p6]Rachel Hornung, Nutan Chen, Patrick van der Smagt
:
Early integration for movement modeling in latent spaces. The Handbook of Multimodal-Multisensor Interfaces, Volume 3 (3) 2019 - [i29]Georgi Dikov, Patrick van der Smagt
, Justin Bayer:
Bayesian Learning of Neural Network Architectures. CoRR abs/1901.04436 (2019) - [i28]Maximilian Soelch, Adnan Akhundov, Patrick van der Smagt, Justin Bayer:
On Deep Set Learning and the Choice of Aggregations. CoRR abs/1903.07348 (2019) - [i27]Alexej Klushyn, Nutan Chen, Richard Kurle, Botond Cseke, Patrick van der Smagt:
Learning Hierarchical Priors in VAEs. CoRR abs/1905.04982 (2019) - [i26]Philip Becker-Ehmck, Jan Peters, Patrick van der Smagt:
Switching Linear Dynamics for Variational Bayes Filtering. CoRR abs/1905.12434 (2019) - [i25]Alexej Klushyn, Nutan Chen, Botond Cseke, Justin Bayer, Patrick van der Smagt:
Increasing the Generalisaton Capacity of Conditional VAEs. CoRR abs/1908.08750 (2019) - [i24]Nutan Chen, Göran Westling, Benoni B. Edin, Patrick van der Smagt:
Estimating Fingertip Forces, Torques, and Local Curvatures from Fingernail Images. CoRR abs/1909.05659 (2019) - [i23]Adnan Akhundov, Maximilian Soelch, Justin Bayer, Patrick van der Smagt
:
Variational Tracking and Prediction with Generative Disentangled State-Space Models. CoRR abs/1910.06205 (2019) - [i22]Neha Das, Maximilian Karl
, Philip Becker-Ehmck, Patrick van der Smagt
:
Beta DVBF: Learning State-Space Models for Control from High Dimensional Observations. CoRR abs/1911.00756 (2019) - 2018
- [c42]Nutan Chen, Alexej Klushyn, Richard Kurle, Xueyan Jiang, Justin Bayer, Patrick van der Smagt
:
Metrics for Deep Generative Models. AISTATS 2018: 1540-1550 - [c41]Nutan Chen, Alexej Klushyn, Alexandros Paraschos, Djalel Benbouzid, Patrick van der Smagt
:
Active Learning based on Data Uncertainty and Model Sensitivity. IROS 2018: 1547-1554 - [i21]Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer:
Approximate Bayesian inference in spatial environments. CoRR abs/1805.07206 (2018) - [i20]Nutan Chen, Alexej Klushyn, Alexandros Paraschos, Djalel Benbouzid, Patrick van der Smagt:
Active Learning based on Data Uncertainty and Model Sensitivity. CoRR abs/1808.02026 (2018) - [i19]Richard Kurle, Stephan Günnemann, Patrick van der Smagt:
Multi-Source Neural Variational Inference. CoRR abs/1811.04451 (2018) - [i18]Nutan Chen, Francesco Ferroni, Alexej Klushyn, Alexandros Paraschos, Justin Bayer, Patrick van der Smagt:
Fast Approximate Geodesics for Deep Generative Models. CoRR abs/1812.08284 (2018) - 2017
- [j18]Egidio Falotico
, Lorenzo Vannucci, Alessandro Ambrosano, Ugo Albanese, Stefan Ulbrich, Juan Camilo Vasquez Tieck
, Georg Hinkel, Jacques Kaiser, Igor Peric, Oliver Denninger, Nino Cauli
, Murat Kirtay, Arne Roennau, Gudrun Klinker
, Axel von Arnim
, Luc Guyot, Daniel Peppicelli, Pablo Martínez-Cañada
, Eduardo Ros, Patrick Maier, Sandro Weber, Manuel Hubert, David A. Plecher, Florian Röhrbein, Stefan Deser, Alina Roitberg, Patrick van der Smagt
, Rüdiger Dillmann, Paul Levi, Cecilia Laschi
, Alois C. Knoll
, Marc-Oliver Gewaltig:
Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform. Frontiers Neurorobotics 11: 2 (2017) - [j17]Hannes Höppner
, Maximilian Große-Dunker, Georg Stillfried, Justin Bayer, Patrick van der Smagt
:
Key Insights into Hand Biomechanics: Human Grip Stiffness Can Be Decoupled from Force by Cocontraction and Predicted from Electromyography. Frontiers Neurorobotics 11: 17 (2017) - [c40]Maximilian Karl, Maximilian Soelch, Justin Bayer, Patrick van der Smagt:
Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data. ICLR (Poster) 2017 - [c39]Jörn Vogel, Naohiro Takemura, Hannes Höppner
, Patrick van der Smagt
, Gowrishankar Ganesh:
Hitting the sweet spot: Automatic optimization of energy transfer during tool-held hits. ICRA 2017: 1549-1556 - [c38]Rui Zhao, Haider Ali, Patrick van der Smagt
:
Two-stream RNN/CNN for action recognition in 3D videos. IROS 2017: 4260-4267 - [i17]Baris Kayalibay, Grady Jensen, Patrick van der Smagt:
CNN-based Segmentation of Medical Imaging Data. CoRR abs/1701.03056 (2017) - [i16]Rui Zhao, Haider Ali, Patrick van der Smagt:
Two-Stream RNN/CNN for Action Recognition in 3D Videos. CoRR abs/1703.09783 (2017) - [i15]Nutan Chen, Alexej Klushyn, Richard Kurle, Xueyan Jiang, Justin Bayer, Patrick van der Smagt:
Metrics for Deep Generative Models. CoRR abs/1711.01204 (2017) - [i14]Sebastian Urban, Patrick van der Smagt:
Automatic Differentiation for Tensor Algebras. CoRR abs/1711.01348 (2017) - [i13]Sebastian Urban, Marcus Basalla, Patrick van der Smagt
:
Gaussian Process Neurons Learn Stochastic Activation Functions. CoRR abs/1711.11059 (2017) - 2016
- [j16]Christoph Richter
, Soren Jentzsch, Rafael Hostettler, Jesús Alberto Garrido, Eduardo Ros, Alois C. Knoll
, Florian Röhrbein, Patrick van der Smagt
, Jörg Conradt:
Musculoskeletal Robots: Scalability in Neural Control. IEEE Robotics Autom. Mag. 23(4): 128-137 (2016) - [c37]Andreas Blenk
, Patrick Kalmbach, Patrick van der Smagt
, Wolfgang Kellerer
:
Boost online virtual network embedding: Using neural networks for admission control. CNSM 2016: 10-18 - [c36]Nutan Chen, Maximilian Karl, Patrick van der Smagt
:
Dynamic movement primitives in latent space of time-dependent variational autoencoders. Humanoids 2016: 629-636 - [c35]Herke van Hoof
, Nutan Chen, Maximilian Karl
, Patrick van der Smagt
, Jan Peters:
Stable reinforcement learning with autoencoders for tactile and visual data. IROS 2016: 3928-3934 - [p5]Patrick van der Smagt
, Michael A. Arbib, Giorgio Metta:
Neurorobotics: From Vision to Action. Springer Handbook of Robotics, 2nd Ed. 2016: 2069-2094 - [i12]Christoph Richter, Sören Jentzsch, Rafael Hostettler, Jesús Alberto Garrido, Eduardo Ros, Alois C. Knoll, Florian Röhrbein, Patrick van der Smagt, Jörg Conradt:
Scalability in Neural Control of Musculoskeletal Robots. CoRR abs/1601.04862 (2016) - [i11]Maximilian Soelch, Justin Bayer, Marvin Ludersdorfer, Patrick van der Smagt:
Variational Inference for On-line Anomaly Detection in High-Dimensional Time Series. CoRR abs/1602.07109 (2016) - [i10]Wiebke Köpp, Patrick van der Smagt, Sebastian Urban:
A Differentiable Transition Between Additive and Multiplicative Neurons. CoRR abs/1604.03736 (2016) - [i9]Maximilian Karl, Maximilian Soelch, Justin Bayer, Patrick van der Smagt:
Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data. CoRR abs/1605.06432 (2016) - [i8]Maximilian Karl, Artur Lohrer, Dhananjay Shah, Frederik Diehl
, Max Fiedler, Saahil Ognawala, Justin Bayer, Patrick van der Smagt:
ML-based tactile sensor calibration: A universal approach. CoRR abs/1606.06588 (2016) - [i7]Maximilian Karl
, Justin Bayer, Patrick van der Smagt:
Unsupervised preprocessing for Tactile Data. CoRR abs/1606.07312 (2016) - 2015
- [j15]Jörn Vogel
, Sami Haddadin
, Beata Jarosiewicz, John D. Simeral, Daniel Bacher, Leigh R. Hochberg, John P. Donoghue, Patrick van der Smagt
:
An assistive decision-and-control architecture for force-sensitive hand-arm systems driven by human-machine interfaces. Int. J. Robotics Res. 34(6): 763-780 (2015) - [c34]Nutan Chen, Justin Bayer, Sebastian Urban, Patrick van der Smagt
:
Efficient movement representation by embedding Dynamic Movement Primitives in deep autoencoders. Humanoids 2015: 434-440 - [c33]Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Häusser, Caner Hazirbas, Vladimir Golkov, Patrick van der Smagt
, Daniel Cremers
, Thomas Brox:
FlowNet: Learning Optical Flow with Convolutional Networks. ICCV 2015: 2758-2766 - [c32]Zoltán Ádám Milacski
, Marvin Ludersdorfer, András Lörincz
, Patrick van der Smagt
:
Robust Detection of Anomalies via Sparse Methods. ICONIP (3) 2015: 419-426 - [c31]Hannes Höppner
, Markus Grebenstein, Patrick van der Smagt
:
Two-dimensional orthoglide mechanism for revealing areflexive human arm mechanical properties. IROS 2015: 1178-1185 - [c30]Nutan Chen, Sebastian Urban, Justin Bayer, Patrick van der Smagt
:
Measuring fingertip forces from camera images for random finger poses. IROS 2015: 1216-1221 - [i6]Sebastian Urban, Patrick van der Smagt:
A Neural Transfer Function for a Smooth and Differentiable Transition Between Additive and Multiplicative Interactions. CoRR abs/1503.05724 (2015) - [i5]Philipp Fischer, Alexey Dosovitskiy, Eddy Ilg, Philip Häusser, Caner Hazirbas, Vladimir Golkov, Patrick van der Smagt, Daniel Cremers, Thomas Brox:
FlowNet: Learning Optical Flow with Convolutional Networks. CoRR abs/1504.06852 (2015) - [i4]Justin Bayer, Maximilian Karl
, Daniela Korhammer, Patrick van der Smagt:
Fast Adaptive Weight Noise. CoRR abs/1507.05331 (2015) - [i3]Maximilian Karl
, Justin Bayer, Patrick van der Smagt:
Efficient Empowerment. CoRR abs/1509.08455 (2015) - 2014
- [c29]Christian Osendorfer, Hubert Soyer, Patrick van der Smagt
:
Image Super-Resolution with Fast Approximate Convolutional Sparse Coding. ICONIP (3) 2014: 250-257 - [c28]Nutan Chen, Sebastian Urban, Christian Osendorfer, Justin Bayer, Patrick van der Smagt
:
Estimating finger grip force from an image of the hand using Convolutional Neural Networks and Gaussian processes. ICRA 2014: 3137-3142 - [c27]Hannes Höppner
, Wolfgang Wiedmeyer, Patrick van der Smagt
:
A new biarticular joint mechanism to extend stiffness ranges. ICRA 2014: 3403-3410 - [c26]Rachel Hornung, Holger Urbanek, Julian Klodmann, Christian Osendorfer, Patrick van der Smagt
:
Model-free robot anomaly detection. IROS 2014: 3676-3683 - [c25]Justin Bayer, Christian Osendorfer, Nutan Chen, Sebastian Urban, Patrick van der Smagt:
On Fast Dropout and its Applicability to Recurrent Networks. ICLR (Poster) 2014 - [p4]Georg Stillfried, Ulrich Hillenbrand, Marcus Settles, Patrick van der Smagt
:
MRI-Based Skeletal Hand Movement Model. The Human Hand as an Inspiration for Robot Hand Development 2014: 49-75 - 2013
- [j14]Claudio Castellini
, Patrick van der Smagt
:
Evidence of muscle synergies during human grasping. Biol. Cybern. 107(2): 233-245 (2013) - [j13]Thomas Rückstieß, Christian Osendorfer, Patrick van der Smagt
:
Minimizing data consumption with sequential online feature selection. Int. J. Mach. Learn. Cybern. 4(3): 235-243 (2013) - [j12]David J. Braun
, Florian Petit, Felix Huber, Sami Haddadin
, Patrick van der Smagt
, Alin Albu-Schäffer
, Sethu Vijayakumar:
Robots Driven by Compliant Actuators: Optimal Control Under Actuation Constraints. IEEE Trans. Robotics 29(5): 1085-1101 (2013) - [c24]Justin Bayer, Christian Osendorfer, Sebastian Urban, Patrick van der Smagt
:
Training Neural Networks with Implicit Variance. ICONIP (2) 2013: 132-139 - [c23]Christian Osendorfer, Justin Bayer, Sebastian Urban, Patrick van der Smagt
:
Convolutional Neural Networks Learn Compact Local Image Descriptors. ICONIP (3) 2013: 624-630 - [c22]Jörn Vogel
, Justin Bayer, Patrick van der Smagt
:
Continuous robot control using surface electromyography of atrophic muscles. IROS 2013: 845-850 - [c21]Sebastian Urban, Justin Bayer, Christian Osendorfer, Göran Westling, Benoni B. Edin, Patrick van der Smagt
:
Computing grip force and torque from finger nail images using Gaussian processes. IROS 2013: 4034-4039 - [c20]Christian Osendorfer, Justin Bayer, Patrick van der Smagt:
Unsupervised Feature Learning for low-level Local Image Descriptors. ICLR (Workshop Poster) 2013 - [i2]Christian Osendorfer, Justin Bayer, Patrick van der Smagt:
Convolutional Neural Networks learn compact local image descriptors. CoRR abs/1304.7948 (2013) - 2012
- [j11]J. Leo van Hemmen, Patrick van der Smagt
, Barry E. Stein:
Foreword for the special issue on Multimodal and Sensorimotor Bionics. Biol. Cybern. 106(11-12): 615-616 (2012) - [j10]Agneta Gustus, Georg Stillfried, Judith Visser, Henrik Jörntell, Patrick van der Smagt
:
Human hand modelling: kinematics, dynamics, applications. Biol. Cybern. 106(11-12): 741-755 (2012) - [c19]Justin Bayer, Christian Osendorfer, Patrick van der Smagt
:
Learning Sequence Neighbourhood Metrics. ICANN (1) 2012: 531-538 - [c18]David J. Braun
, Florian Petit, Felix Huber, Sami Haddadin
, Patrick van der Smagt
, Alin Albu-Schäffer
, Sethu Vijayakumar:
Optimal torque and stiffness control in compliantly actuated robots. IROS 2012: 2801-2808 - [c17]Dominic Lakatos, Daniel Rüschen
, Justin Bayer, Jörn Vogel, Patrick van der Smagt
:
Identification of Human Limb Stiffness in 5 DoF and Estimation via EMG. ISER 2012: 89-99 - [p3]Patrick van der Smagt
, Gerd Hirzinger:
Solving the Ill-Conditioning in Neural Network Learning. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 191-203 - 2011
- [c16]Thomas Rückstieß, Christian Osendorfer, Patrick van der Smagt
:
Sequential Feature Selection for Classification. Australasian Conference on Artificial Intelligence 2011: 132-141 - [c15]Dominic Lakatos, Florian Petit, Patrick van der Smagt
:
Conditioning vs. excitation time for estimating impedance parameters of the human arm. Humanoids 2011: 636-642 - [c14]Claudio Castellini
, Patrick van der Smagt
:
Preliminary evidence of dynamic muscular synergies in human grasping. ICAR 2011: 28-33 - [c13]Hannes Höppner
, Dominic Lakatos, Holger Urbanek, Claudio Castellini
, Patrick van der Smagt
:
The Grasp Perturbator: Calibrating human grasp stiffness during a graded force task. ICRA 2011: 3312-3316 - [c12]Jörn Vogel, Claudio Castellini, Patrick van der Smagt
:
EMG-based teleoperation and manipulation with the DLR LWR-III. IROS 2011: 672-678 - [i1]Justin Bayer, Christian Osendorfer, Patrick van der Smagt:
Learning Sequence Neighbourhood Metrics. CoRR abs/1109.2034 (2011) - 2010
- [c11]Michael Strohmayr, Hannes P. Saal
, Abhijit Potdar, Patrick van der Smagt
:
The DLR touch sensor I: A flexible tactile sensor for robotic hands based on a crossed-wire approach. IROS 2010: 897-903 - [c10]Joern Vogel
, Sami Haddadin
, John D. Simeral, Sergey D. Stavisky
, Daniel Bacher, Leigh R. Hochberg
, John P. Donoghue, Patrick van der Smagt
:
Continuous Control of the DLR Light-Weight Robot III by a Human with Tetraplegia Using the BrainGate2 Neural Interface System. ISER 2010: 125-136
2000 – 2009
- 2009
- [j9]Claudio Castellini
, Patrick van der Smagt
:
Surface EMG in advanced hand prosthetics. Biol. Cybern. 100(1): 35-47 (2009) - 2008
- [j8]Markus Grebenstein
, Patrick van der Smagt
:
Antagonism for a Highly Anthropomorphic Hand-Arm System. Adv. Robotics 22(1): 39-55 (2008) - [c9]Claudio Castellini
, Patrick van der Smagt
, Giulio Sandini, Gerd Hirzinger:
Surface EMG for force control of mechanical hands. ICRA 2008: 725-730 - [p2]Michael A. Arbib, Giorgio Metta, Patrick van der Smagt
:
Neurorobotics: From Vision to Action. Springer Handbook of Robotics 2008: 1453-1480 - 2006
- [c8]Sebastian Bitzer, Patrick van der Smagt
:
Learning EMG Control of a Robotic Hand: Towards Active Prostheses. ICRA 2006: 2819-2823 - 2004
- [c7]Holger Urbanek, Alin Albu-Schäffer, Patrick van der Smagt
:
Learning from demonstration: repetitive movements for autonomous service robotics. IROS 2004: 3495-3500 - 2002
- [j7]Patrick van der Smagt
, Daniel Bullock:
Guest Editorial for Special Issue on Scalable Applications of Neural Networks to Robotics. Appl. Intell. 17(1): 7-10 (2002) - [j6]Jan Peters, Patrick van der Smagt
:
Searching a Scalable Approach to Cerebellar Based Control. Appl. Intell. 17(1): 11-33 (2002) - 2000
- [j5]Patrick van der Smagt
:
Benchmarking cerebellar control. Robotics Auton. Syst. 32(4): 237-251 (2000) - [c6]Patrick van der Smagt
, Gerd Hirzinger:
The cerebellum as computed torque model. KES 2000: 760-763
1990 – 1999
- 1998
- [j4]Patrick van der Smagt
:
Cerebellar Control of Robot Arms. Connect. Sci. 10(3-4): 301-320 (1998) - [c5]Max Fischer, Patrick van der Smagt
, Gerd Hirzinger:
Learning Techniques in a Dataglove Based Telemanipulation System for the DLR Hand. ICRA 1998: 1603-1608 - 1996
- [j3]Patrick van der Smagt
, Frans C. A. Groen, Klaus Schulten:
Analysis and control of a rubbertuator arm. Biol. Cybern. 75(5): 433-440 (1996) - [p1]Patrick van der Smagt
, Gerd Hirzinger:
Solving the Ill-Conditioning in Neural Network Learning. Neural Networks: Tricks of the Trade 1996: 193-206 - 1995
- [c4]Patrick van der Smagt
, Frans C. A. Groen:
Approximation with neural networks: between local and global approximation. ICNN 1995: 1060-1064 - [c3]Patrick van der Smagt
, Anuj Dev, Frans C. A. Groen:
A visually guided robot and a neural network join to grasp slanted objects. SNN Symposium on Neural Networks 1995: 121-128 - 1994
- [j2]P. Patrick van der Smagt
:
Minimisation methods for training feedforward neural networks. Neural Networks 7(1): 1-11 (1994) - [j1]Ted Hesselroth, Kakali Sarkar, P. Patrick van der Smagt
, Klaus Schulten:
Neural Network Control of a Pneumatic Robot Arm. IEEE Trans. Syst. Man Cybern. Syst. 24(1): 28-38 (1994) - 1992
- [c2]P. Patrick van der Smagt
, Ben J. A. Kröse, Frans C. A. Groen:
A Self-learning Controller For Monocular Grasping. IROS 1992: 177-181 - 1990
- [c1]P. Patrick van der Smagt
:
A Comparative Study of Neural Network Algorithms Applied to Optical Character Recognition. IEA/AIE (Vol. 2) 1990: 1037-1044
Coauthor Index
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