Hofmann, Katja

Automatic Curriculum Learning For Deep RL: A Short Survey

Portelas, R., Colas, C., Weng, L., Hofmann, K., & Oudeyer, P.-Y. (2020) · Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 127

VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning

Zintgraf, L., Shiarlis, K., Igl, M., Schulze, S., Gal, Y., Hofmann, K., & Whiteson, S. (2019) · arXiv

Reinforcement Learning in RoboticsAdvanced Bandit Algorithms Research

Cited by 112

Meta Reinforcement Learning with Latent Variable Gaussian Processes

Sæmundsson, S., Hofmann, K., & Deisenroth, M. P. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 106

Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments

Portelas, R., Colas, C., Hofmann, K., & Oudeyer, P.-Y. (2019) · arXiv

Reinforcement Learning in RoboticsAdvanced Bandit Algorithms Research

Cited by 59

The MineRL 2019 Competition on Sample Efficient Reinforcement Learning using Human Priors

Guss, W. H., Codel, C., Hofmann, K., Houghton, B., Kuno, N., Milani, S., Mohanty, S., Liebana, D. P., Salakhutdinov, R., Topin, N., et al. (2019) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 46

Disability-first Dataset Creation: Lessons from Constructing a Dataset for Teachable Object Recognition with Blind and Low Vision Data Collectors

Theodorou, L., Massiceti, D., Zintgraf, L., Stumpf, S., Morrison, C., Cutrell, E., Harris, M. T., & Hofmann, K. (2021) · Proceedings of the 23rd International ACM SIGACCESS Conference on Computers and Accessibility

Assistive Technology in Communication and MobilityDigital Accessibility for Disabilities

Cited by 42

ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition

Massiceti, D., Zintgraf, L., Bronskill, J., Theodorou, L., Harris, M. T., Cutrell, E., Morrison, C., Hofmann, K., & Stumpf, S. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 33

Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning

Janz, D., Hron, J., Mazur, P., Hofmann, K., Hernández-Lobato, J. M., & Tschiatschek, S. (2018) · arXiv

Reinforcement Learning in RoboticsAdvanced Bandit Algorithms Research

Cited by 23