77 citations · 108 across the 6 of their papers we have counts for
4 papers · 1 filter
Normalized Attention Without Probability Cage
Oliver Richter, Roger Wattenhofer
Attention architectures are widely used; they recently gained renewed popularity with Transformers yielding a streak of state of the art results. Yet, the geometrical implications…
Attentive Multi-Task Deep Reinforcement Learning
Timo Bram, Gino Brunner, Oliver Richter +1
Sharing knowledge between tasks is vital for efficient learning in a multi-task setting. However, most research so far has focused on the easier case where knowledge transfer is no…
Learning Policies through Quantile Regression
Oliver Richter, Roger Wattenhofer
Policy gradient based reinforcement learning algorithms coupled with neural networks have shown success in learning complex policies in the model free continuous action space contr…
Using State Predictions for Value Regularization in Curiosity Driven Deep Reinforcement Learning
Gino Brunner, Manuel Fritsche, Oliver Richter +1
Learning in sparse reward settings remains a challenge in Reinforcement Learning, which is often addressed by using intrinsic rewards. One promising strategy is inspired by human c…