Scalable deep learning to identify brick kilns and aid regulatory capacity von Lee, Jihyeon, Brooks, Nina R., Tajwar, Fahim, Burke, Marshall, Ermon, Stefano, Lobell, David B., Biswas, Debashish, Luby, Stephen P.

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Conservative Prediction via Data-Driven Confidence Minimization von Choi, Caroline, Tajwar, Fahim, Lee, Yoonho, Yao, Huaxiu, Kumar, Ananya, Finn, Chelsea

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Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data von Tajwar, Fahim, Singh, Anikait, Sharma, Archit, Rafailov, Rafael, Schneider, Jeff, Xie, Tengyang, Ermon, Stefano, Finn, Chelsea, Kumar, Aviral

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No True State-of-the-Art? OOD Detection Methods are Inconsistent across Datasets von Tajwar, Fahim, Kumar, Ananya, Xie, Sang Michael, Liang, Percy

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Do Deep Networks Transfer Invariances Across Classes? von Zhou, Allan, Tajwar, Fahim, Robey, Alexander, Knowles, Tom, Pappas, George J, Hassani, Hamed, Finn, Chelsea

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Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data von Fahim Tajwar, Singh, Anikait, Sharma, Archit, Rafailov, Rafael, Schneider, Jeff, Xie, Tengyang, Ermon, Stefano, Finn, Chelsea, Kumar, Aviral

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Replication Data for: Scalable deep learning to identify brick kilns and aid regulatory capacity von Lee, Jihyeon, Brooks, Nina, Tajwar, Fahim, Burke, Marshall, Ermon, Stefano, Lobell, David, Biswas, Debashish, Luby, Stephen

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