Motion Perception in Reinforcement Learning with Dynamic Objects. - Artemij Amiranashvili; Alexey Dosovitskiy; Vladlen Koltun; Thomas Brox (CoRL, 2018)

TD or not TD: Analyzing the Role of Temporal Differencing in Deep Reinforcement Learning. - Artemij Amiranashvili; Alexey Dosovitskiy; Vladlen Koltun; Thomas Brox (ICLR (Poster), 2018)

Adaptive Curriculum Generation from Demonstrations for Sim-to-Real Visuomotor Control. - Lukás Hermann; Max Argus; Andreas Eitel; Artemij Amiranashvili; Wolfram Burgard; Thomas Brox (ICRA, 2020)

Scaling Imitation Learning in Minecraft. - Artemij Amiranashvili; Nicolai Dorka; Wolfram Burgard; Vladlen Koltun; Thomas Brox (CoRR, 2020)

Pre-training of Deep RL Agents for Improved Learning under Domain Randomization. - Artemij Amiranashvili; Max Argus; Lukás Hermann; Wolfram Burgard; Thomas Brox (CoRR, 2021)

A Benchmark and a Baseline for Robust Multi-view Depth Estimation. - Philipp Schröppel; Jan Bechtold; Artemij Amiranashvili; Thomas Brox (3DV, 2022)

CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity. - Aditya Bhatt 001; Daniel Palenicek; Boris Belousov; Max Argus; Artemij Amiranashvili; Thomas Brox; Jan Peters 001 (ICLR, 2024)