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ORCIDPatrick van der Smagt
P. Patrick van der Smagt
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- affiliation: German Aerospace Center, Germany
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Journal Articles
- 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)- 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 1998
- [j4]Patrick van der Smagt:
Cerebellar Control of Robot Arms. Connect. Sci. 10(3-4): 301-320 (1998) - 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) - 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)
Conference and Workshop Papers
- 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - 2008
- [c9]Claudio Castellini, Patrick van der Smagt, Giulio Sandini, Gerd Hirzinger:
Surface EMG for force control of mechanical hands. ICRA 2008: 725-730 - 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 - 2000
- [c6]Patrick van der Smagt, Gerd Hirzinger:
The cerebellum as computed torque model. KES 2000: 760-763 - 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 - 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 - 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
Parts in Books or Collections
- 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 - 2016
- [p5]Patrick van der Smagt, Michael A. Arbib, Giorgio Metta:
Neurorobotics: From Vision to Action. Springer Handbook of Robotics, 2nd Ed. 2016: 2069-2094 - 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 - 2012
- [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 - 2008
- [p2]Michael A. Arbib, Giorgio Metta, Patrick van der Smagt:
Neurorobotics: From Vision to Action. Springer Handbook of Robotics 2008: 1453-1480 - 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
Informal and Other Publications
- 2024
- [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
- [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
- [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
- [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
- [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) - 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
- [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
- [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
- [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
- [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) - 2013
- [i2]Christian Osendorfer, Justin Bayer, Patrick van der Smagt:
Convolutional Neural Networks learn compact local image descriptors. CoRR abs/1304.7948 (2013) - 2011
- [i1]Justin Bayer, Christian Osendorfer, Patrick van der Smagt:
Learning Sequence Neighbourhood Metrics. CoRR abs/1109.2034 (2011)
Coauthor Index
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