Todor Davchev
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Model-Based Inverse Reinforcement Learning from Visual Demonstrations
N Das, S Bechtle, T Davchev, D Jayaraman, A Rai, F Meier
CoRL 2020, 2020
Vid2Param: Modelling of Dynamics Parameters from Video
M Asenov, M Burke, D Angelov, TB Davchev, K Subr, S Ramamoorthy
IEEE Robotics and Automation Letters (ICRA), 2019
Residual Learning from Demonstration: Adapting DMPs for Contact-rich Manipulation
T Davchev, KS Luck, M Burke, F Meier, S Schaal, S Ramamoorthy
IEEE Robotics and Automation Letters 7 (2), 4488-4495, 2022
An Empirical Evaluation of Adversarial Robustness under Transfer Learning
T Davchev, T Kores, S Fotiadis, N Antonopoulos, S Ramamoorthy
ICML 2019 Understanding and Improving Generalisation Workshop, 2019
Learning Structured Representations of Spatial and Interactive Dynamics for Trajectory Prediction in Crowded Scenes
T Davchev, M Burke, S Ramamoorthy
IEEE Robotics and Automation Letters 6 (2), 707-714, 2020
Wish you were here: Hindsight Goal Selection for long-horizon dexterous manipulation
T Davchev, O Sushkov, JB Regli, S Schaal, Y Aytar, M Wulfmeier, ...
International Conference on Learning Representations (ICLR), 2022
Learning Time-Invariant Reward Functions through Model-Based Inverse Reinforcement Learning
T Davchev, S Bechtle, S Ramamoorthy, F Meier
arXiv preprint arXiv:2107.03186, 2021
Modelling Entailment with Neural Networks
T Davchev, 2016
Crowded Scene Training/Inference and Useful Tricks
T Davchev
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