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ORCIDCody Wild
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2020 – today
- 2024
[i10]Cody Wild, Jesper Anderson:
Uncovering Layer-Dependent Activation Sparsity Patterns in ReLU Transformers. CoRR abs/2407.07848 (2024)- 2022
- [i9]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:
Retrospective on the 2021 BASALT Competition on Learning from Human Feedback. CoRR abs/2204.07123 (2022) - [i8]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:
An Empirical Investigation of Representation Learning for Imitation. CoRR abs/2205.07886 (2022) - 2021
- [c5]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:
An Empirical Investigation of Representation Learning for Imitation. NeurIPS Datasets and Benchmarks 2021 - [c4]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:
Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback. NeurIPS (Competition and Demos) 2021: 259-272 - [i7]Daniel Filan, Stephen Casper, Shlomi Hod, Cody Wild, Andrew Critch, Stuart Russell:
Clusterability in Neural Networks. CoRR abs/2103.03386 (2021) - [i6]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:
The MineRL BASALT Competition on Learning from Human Feedback. CoRR abs/2107.01969 (2021) - [i5]Shlomi Hod, Stephen Casper, Daniel Filan, Cody Wild, Andrew Critch, Stuart Russell:
Detecting Modularity in Deep Neural Networks. CoRR abs/2110.08058 (2021) - 2020
- [c3]Adam Gleave, Michael Dennis, Cody Wild, Neel Kant, Sergey Levine, Stuart Russell:
Adversarial Policies: Attacking Deep Reinforcement Learning. ICLR 2020 - [i4]Daniel Filan, Shlomi Hod, Cody Wild, Andrew Critch, Stuart Russell:
Neural Networks are Surprisingly Modular. CoRR abs/2003.04881 (2020)
2010 – 2019
- 2019
- [c2]Ethan M. Rudd, Felipe N. Ducau, Cody Wild, Konstantin Berlin, Richard E. Harang:
ALOHA: Auxiliary Loss Optimization for Hypothesis Augmentation. USENIX Security Symposium 2019: 303-320 - [i3]Ethan M. Rudd, Felipe N. Ducau, Cody Wild, Konstantin Berlin, Richard E. Harang:
ALOHA: Auxiliary Loss Optimization for Hypothesis Augmentation. CoRR abs/1903.05700 (2019) - [i2]Adam Gleave, Michael Dennis, Neel Kant, Cody Wild, Sergey Levine, Stuart Russell:
Adversarial Policies: Attacking Deep Reinforcement Learning. CoRR abs/1905.10615 (2019) - 2018
- [c1]Joshua Saxe, Richard E. Harang, Cody Wild, Hillary Sanders:
A Deep Learning Approach to Fast, Format-Agnostic Detection of Malicious Web Content. IEEE Symposium on Security and Privacy Workshops 2018: 8-14 - [i1]Joshua Saxe, Richard E. Harang, Cody Wild, Hillary Sanders:
A Deep Learning Approach to Fast, Format-Agnostic Detection of Malicious Web Content. CoRR abs/1804.05020 (2018)
Coauthor Index
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