Search Results for author: Zachary Polizzi

Found 3 papers, 1 papers with code

Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds

no code implementations24 Oct 2022 Joshua Albrecht, Abraham J. Fetterman, Bryden Fogelman, Ellie Kitanidis, Bartosz Wróblewski, Nicole Seo, Michael Rosenthal, Maksis Knutins, Zachary Polizzi, James B. Simon, Kanjun Qiu

As a benchmark tailored for studying RL generalization, we introduce Avalon, a set of tasks in which embodied agents in highly diverse procedural 3D worlds must survive by navigating terrain, hunting or gathering food, and avoiding hazards.


FusedProp: Towards Efficient Training of Generative Adversarial Networks

1 code implementation30 Mar 2020 Zachary Polizzi, Chuan-Yung Tsai

Generative adversarial networks (GANs) are capable of generating strikingly realistic samples but state-of-the-art GANs can be extremely computationally expensive to train.

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