Cody Wild

According to our database, Cody Wild authored at least 12 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Uncovering Layer-Dependent Activation Sparsity Patterns in ReLU Transformers.

Cody Wild, Jesper Anderson

CoRR, 2024

2022

An Empirical Investigation of Representation Learning for Imitation.

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

CoRR, 2022

Retrospective on the 2021 BASALT Competition on Learning from Human Feedback.

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

CoRR, 2022

2021

Detecting Modularity in Deep Neural Networks.

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

CoRR, 2021

The MineRL BASALT Competition on Learning from Human Feedback.

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

CoRR, 2021

Clusterability in Neural Networks.

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

CoRR, 2021

Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback.

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

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

An Empirical Investigation of Representation Learning for Imitation.

Cynthia Chen, 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

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020

Neural Networks are Surprisingly Modular.

Daniel Filan, Shlomi Hod, Cody Wild, Andrew Critch, Stuart Russell

CoRR, 2020

Adversarial Policies: Attacking Deep Reinforcement Learning.

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

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

ALOHA: Auxiliary Loss Optimization for Hypothesis Augmentation.

Ethan M. Rudd, Felipe N. Ducau, Cody Wild, Konstantin Berlin, Richard E. Harang

Proceedings of the 28th USENIX Security Symposium, 2019

2018

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

Joshua Saxe, Richard E. Harang, Cody Wild, Hillary Sanders

Proceedings of the 2018 IEEE Security and Privacy Workshops, 2018