| CARVIEW |
Davchev, Todor, Oleg Sushkov, Jean-baptiste Regli, Stefan Schaal, Yusuf Aytar, Markus Wulfmeier, Jon Scholz. "Wish you were here: Hindsight Goal Selection for Long-horizon Dexterous Manipulation." International Conference on Learning Representations (ICLR) 2022.
Davchev, Todor, Michael Burke, and Subramanian Ramamoorthy. "Learning Structured Representations of Spatial and Interactive Dynamics for Trajectory Prediction in Crowded Scenes." IEEE Robotics and Automation Letters 6, no. 2 (2020): 707-714.
Davchev, Todor, Sarah Bechtle, Subramanian Ramamoorthy, and Franziska Meier. "Learning Time-Invariant Reward Functions through Model-Based Inverse Reinforcement Learning." arXiv preprint arXiv:2107.03186 (2021).
Das, N., Bechtle, S., Davchev, T., Jayaraman, D., Rai, A. and Meier, F., 2020. Model-Based Inverse Reinforcement Learning from Visual Demonstrations. Conference on Robot Learning (CoRL) 2020.
Davchev, T., Luck, K.S., Burke, M., Meier, F., Schaal, S. and Ramamoorthy, S., 2020. Residual Learning from Demonstration. arXiv preprint arXiv:2008.07682.
Asenov, M., Burke, M., Angelov, D., Davchev, T., Subr, K. and Ramamoorthy, S., 2019. Vid2param: Modeling of dynamics parameters from video. IEEE Robotics and Automation Letters, 5(2), pp.414-421.
Davchev, T., Korres, T., Fotiadis, S., Antonopoulos, N. and Ramamoorthy, S., 2019. An empirical evaluation of adversarial robustness under transfer learning. International Conference on Machine Learning (ICML) 2019, Understanding and Improving Generalization Workshop.
Davchev, Todor. (2016). Modelling Entailment with Neural Networks. MSc Thesis. University of Edinburgh.
