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Cody Wild

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An Empirical Investigation of Representation Learning for Imitation

May 16, 2022
Xin Chen, Sam Toyer, Cody Wild, Scott Emmons, Ian Fischer, Kuang-Huei Lee, Neel Alex, Steven H Wang, Ping Luo, Stuart Russell, Pieter Abbeel, Rohin Shah

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Retrospective on the 2021 BASALT Competition on Learning from Human Feedback

Apr 14, 2022
Rohin Shah, Steven H. Wang, Cody Wild, Stephanie Milani, Anssi Kanervisto, Vinicius G. Goecks, Nicholas Waytowich, David Watkins-Valls, Bharat Prakash, Edmund Mills, Divyansh Garg, Alexander Fries, Alexandra Souly, Chan Jun Shern, Daniel del Castillo, Tom Lieberum

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Detecting Modularity in Deep Neural Networks

Oct 13, 2021
Shlomi Hod, Stephen Casper, Daniel Filan, Cody Wild, Andrew Critch, Stuart Russell

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The MineRL BASALT Competition on Learning from Human Feedback

Jul 05, 2021
Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William Guss, Sharada Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, Pieter Abbeel, Stuart Russell, Anca Dragan

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Clusterability in Neural Networks

Mar 04, 2021
Daniel Filan, Stephen Casper, Shlomi Hod, Cody Wild, Andrew Critch, Stuart Russell

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Neural Networks are Surprisingly Modular

Mar 11, 2020
Daniel Filan, Shlomi Hod, Cody Wild, Andrew Critch, Stuart Russell

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Adversarial Policies: Attacking Deep Reinforcement Learning

May 25, 2019
Adam Gleave, Michael Dennis, Neel Kant, Cody Wild, Sergey Levine, Stuart Russell

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ALOHA: Auxiliary Loss Optimization for Hypothesis Augmentation

Mar 13, 2019
Ethan M. Rudd, Felipe N. Ducau, Cody Wild, Konstantin Berlin, Richard Harang

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A Deep Learning Approach to Fast, Format-Agnostic Detection of Malicious Web Content

Apr 13, 2018
Joshua Saxe, Richard Harang, Cody Wild, Hillary Sanders

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