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ORCIDVihang Patil
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- affiliation: Johannes Kepler University Linz, Institute for Machine Learning, Linz, Austria
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2020 – today
- 2022
[c7]Youssef Diouane, Aurélien Lucchi, Vihang Prakash Patil:
A Globally Convergent Evolutionary Strategy for Stochastic Constrained Optimization with Applications to Reinforcement Learning. AISTATS 2022: 836-859- [c6]Christian Alexander Steinparz, Thomas Schmied, Fabian Paischer, Marius-Constantin Dinu, Vihang Prakash Patil, Angela Bitto-Nemling, Hamid Eghbal-zadeh, Sepp Hochreiter:
Reactive Exploration to Cope With Non-Stationarity in Lifelong Reinforcement Learning. CoLLAs 2022: 441-469 - [c5]Kajetan Schweighofer, Marius-Constantin Dinu, Andreas Radler, Markus Hofmarcher, Vihang Prakash Patil, Angela Bitto-Nemling, Hamid Eghbal-zadeh, Sepp Hochreiter:
A Dataset Perspective on Offline Reinforcement Learning. CoLLAs 2022: 470-517 - [c4]Fabian Paischer, Thomas Adler, Vihang Patil, Angela Bitto-Nemling, Markus Holzleitner, Sebastian Lehner, Hamid Eghbal-Zadeh, Sepp Hochreiter:
History Compression via Language Models in Reinforcement Learning. ICML 2022: 17156-17185 - [c3]Vihang Patil, Markus Hofmarcher, Marius-Constantin Dinu, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, José Antonio Arjona-Medina, Sepp Hochreiter:
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution. ICML 2022: 17531-17572 - [i5]Youssef Diouane, Aurélien Lucchi, Vihang Patil:
A Globally Convergent Evolutionary Strategy for Stochastic Constrained Optimization with Applications to Reinforcement Learning. CoRR abs/2202.10464 (2022) - [i4]Fabian Paischer, Thomas Adler, Vihang Patil, Angela Bitto-Nemling, Markus Holzleitner, Sebastian Lehner, Hamid Eghbal-zadeh, Sepp Hochreiter:
History Compression via Language Models in Reinforcement Learning. CoRR abs/2205.12258 (2022) - [i3]Christian Alexander Steinparz
, Thomas Schmied, Fabian Paischer, Marius-Constantin Dinu, Vihang Patil, Angela Bitto-Nemling, Hamid Eghbal-zadeh, Sepp Hochreiter:
Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning. CoRR abs/2207.05742 (2022) - 2021
- [c2]Vittorio Caggiano, Guillaume Durandau, Huawei Wang, Alberto Silvio Chiappa, Alexander Mathis, Pablo Tano, Nisheet Patel, Alexandre Pouget, Pierre Schumacher, Georg Martius, Daniel F. B. Haeufle, Yiran Geng, Boshi An, Yifan Zhong, Jiaming Ji, Yuanpei Chen, Hao Dong, Yaodong Yang, Rahul Siripurapu, Luis Eduardo Ferro Diez, Michael Kopp, Vihang Patil, Sepp Hochreiter, Yuval Tassa, Josh Merel, Randy Schultheis, Seungmoon Song, Massimo Sartori, Vikash Kumar:
MyoChallenge 2022: Learning contact-rich manipulation using a musculoskeletal hand. NeurIPS (Competition and Demos) 2021: 233-250 - [i2]Kajetan Schweighofer, Markus Hofmarcher, Marius-Constantin Dinu, Philipp Renz, Angela Bitto-Nemling, Vihang Patil, Sepp Hochreiter:
Understanding the Effects of Dataset Characteristics on Offline Reinforcement Learning. CoRR abs/2111.04714 (2021) - 2020
- [c1]Marius-Constantin Dinu, Markus Hofmarcher, Vihang Prakash Patil, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, Jose A. Arjona-Medina, Sepp Hochreiter:
XAI and Strategy Extraction via Reward Redistribution. xxAI@ICML 2020: 177-205 - [i1]Vihang Prakash Patil, Markus Hofmarcher, Marius-Constantin Dinu, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, Jose A. Arjona-Medina, Sepp Hochreiter:
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution. CoRR abs/2009.14108 (2020)
Coauthor Index
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