Thomas Schmied

发表

Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning

Vihang P. Patil, S. Hochreiter, Hamid Eghbal-zadeh, 2022, CoLLAs.

R EACTIVE E XPLORATION TO C OPE WITH N ON -S TATIONARITY IN L IFELONG R EINFORCEMENT L EARNING

Vihang P. Patil, S. Hochreiter, Hamid Eghbal-zadeh, 2022 .

Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning

Vihang P. Patil, S. Hochreiter, Hamid Eghbal-zadeh, 2022, CoLLAs.

Fast and Data-Efficient Training of Rainbow: an Experimental Study on Atari pdf

Dominik Schmidt, Thomas Schmied, Dominik Schmidt, 2021, ArXiv.

Learning to Modulate pre-trained Models in RL

S. Hochreiter, Razvan Pascanu, M. Hofmarcher, 2023, ArXiv.

InfODist: Online distillation with Informative rewards improves generalization in Curriculum Learning

S. Hochreiter, Markus Holzleitner, Michael Kopp, 2022 .

Efﬁcient Reinforcement Learning via Self-supervised learning and Model-based methods

Thomas Schmied, TU Wien, Maximilian Thiessen, 2020 .

Learning to Modulate pre-trained Models in RL

S. Hochreiter, Razvan Pascanu, M. Hofmarcher, 2023, NeurIPS.