Lerchner, Alexander

MONet: Unsupervised Scene Decomposition and Representation

Burgess, C. P., Matthey, L., Watters, N., Kabra, R., Higgins, I., Botvinick, M., & Lerchner, A. (2019) · arXiv

Advanced Neural Network ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 270

Darla Improving zero-shot transfer in reinforcement learning

Higgins, I., Pal, A., Rusu, A. A., Matthey, L., Burgess, C. P., Pritzel, A., Botvinick, M., Blundell, C., & Lerchner, A. (2017) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 219

Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents

Wang, J. X., King, M., Porcel, N., Kurth-Nelson, Z., Zhu, T., Deck, C., Choy, P., Cassin, M., Reynolds, M., Song, F., et al. (2021) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 10

Scaling Instructable Agents Across Many Simulated Worlds

SIMA Team, Raad, M. A., Ahuja, A., Barros, C., Besse, F., Bolt, A., Bolton, A., Brownfield, B., Buttimore, G., Cant, M., et al. (2024) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 9