2 code implementations • 9 Nov 2015 • Shiry Ginosar, Kate Rakelly, Sarah Sachs, Brian Yin, Crystal Lee, Philipp Krahenbuhl, Alexei A. Efros
4) A new method for discovering and displaying the visual elements used by the CNN-based date-prediction model to date portraits, finding that they correspond to the tell-tale fashions of each era.
1 code implementation • 11 Aug 2016 • Evan Shelhamer, Kate Rakelly, Judy Hoffman, Trevor Darrell
Recent years have seen tremendous progress in still-image segmentation; however the na\"ive application of these state-of-the-art algorithms to every video frame requires considerable computation and ignores the temporal continuity inherent in video.
1 code implementation • 25 May 2018 • Kate Rakelly, Evan Shelhamer, Trevor Darrell, Alexei A. Efros, Sergey Levine
Learning-based methods for visual segmentation have made progress on particular types of segmentation tasks, but are limited by the necessary supervision, the narrow definitions of fixed tasks, and the lack of control during inference for correcting errors.
7 code implementations • ICLR Workshop LLD 2019 • Kate Rakelly, Aurick Zhou, Deirdre Quillen, Chelsea Finn, Sergey Levine
In our approach, we perform online probabilistic filtering of latent task variables to infer how to solve a new task from small amounts of experience.
1 code implementation • 26 Oct 2020 • Tony Z. Zhao, Anusha Nagabandi, Kate Rakelly, Chelsea Finn, Sergey Levine
Meta-reinforcement learning algorithms can enable autonomous agents, such as robots, to quickly acquire new behaviors by leveraging prior experience in a set of related training tasks.
no code implementations • NeurIPS 2021 • Kate Rakelly, Abhishek Gupta, Carlos Florensa, Sergey Levine
Mutual information maximization provides an appealing formalism for learning representations of data.