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https://github.com/ajaysub110/paper-a-day
keeps the doctor away
https://github.com/ajaysub110/paper-a-day
Last synced: about 1 month ago
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keeps the doctor away
- Host: GitHub
- URL: https://github.com/ajaysub110/paper-a-day
- Owner: ajaysub110
- Created: 2020-11-13T04:19:25.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2020-12-07T05:49:22.000Z (about 4 years ago)
- Last Synced: 2024-12-05T17:22:32.285Z (about 1 month ago)
- Size: 5.86 KB
- Stars: 0
- Watchers: 4
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Reading list
**Model-based RL**
Hafner, Danijar, Timothy Lillicrap, Mohammad Norouzi, and Jimmy Ba. “Mastering Atari with Discrete World Models.” ArXiv:2010.02193 [Cs, Stat], October 5, 2020. http://arxiv.org/abs/2010.02193.
**Cognitive Science / Neuro-Symbolic**
Cranmer, Miles, Alvaro Sanchez-Gonzalez, Peter Battaglia, Rui Xu, Kyle Cranmer, David Spergel, and Shirley Ho. “Discovering Symbolic Models from Deep Learning with Inductive Biases,” n.d., 14.
Anonymous. “HALMA: Humanlike Abstraction Learning Meets Affordance in Rapid Problem Solving,” 2020. https://openreview.net/forum?id=D51irFX8UOG.
Lake, Brenden M., Tomer D. Ullman, Joshua B. Tenenbaum, and Samuel J. Gershman. “Building Machines That Learn and Think Like People.” ArXiv:1604.00289 [Cs, Stat], November 2, 2016. http://arxiv.org/abs/1604.00289.
**Neuroscience**
Richards, Blake A. “Moving beyond Reward Prediction Errors.” Nature Machine Intelligence 1, no. 5 (May 2019): 204–5. https://doi.org/10.1038/s42256-019-0053-0.
**Representation Learning**
Le-Khac, Phuc H., Graham Healy, and Alan F. Smeaton. “Contrastive Representation Learning: A Framework and Review.” IEEE Access 8 (2020): 193907–34. https://doi.org/10.1109/ACCESS.2020.3031549.
**Multi-Agent RL**
Xie, Annie, Dylan P. Losey, Ryan Tolsma, Chelsea Finn, and Dorsa Sadigh. “Learning Latent Representations to Influence Multi-Agent Interaction.” ArXiv:2011.06619 [Cs], November 12, 2020. http://arxiv.org/abs/2011.06619.