Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models | 0 | 0.34 | 2021 |
SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments | 0 | 0.34 | 2021 |
Conservative Safety Critics for Exploration | 0 | 0.34 | 2021 |
Parrot: Data-Driven Behavioral Priors for Reinforcement Learning | 0 | 0.34 | 2021 |
Deep Imitative Models for Flexible Inference, Planning, and Control | 1 | 0.35 | 2020 |
Can autonomous vehicles identify, recover from, and adapt to distribution shifts? | 0 | 0.34 | 2020 |
Generative Hybrid Representations for Activity Forecasting With No-Regret Learning | 0 | 0.34 | 2019 |
Precog: Prediction Conditioned On Goals In Visual Multi-Agent Settings | 4 | 0.51 | 2019 |
Directed-Info GAIL: Learning Hierarchical Policies from Unsegmented Demonstrations using Directed Information | 1 | 0.35 | 2019 |
N2N Learning: Network to Network Compression via Policy Gradient Reinforcement Learning. | 10 | 0.49 | 2017 |
Predictive-State Decoders: Encoding the Future into Recurrent Networks. | 3 | 0.37 | 2017 |
Learning Action Maps of Large Environments via First-Person Vision | 8 | 0.41 | 2016 |
Visual Chunking: A List Prediction Framework for Region-Based Object Detection. | 1 | 0.37 | 2014 |