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2020 – today
- 2025
[c3]Jon Saad-Falcon, Adrian Gamarra Lafuente, Shlok Natarajan, Nahum Maru, Hristo Todorov, Etash Kumar Guha, Estefany Kelly Buchanan, Mayee F. Chen, Neel Guha, Christopher Ré, Azalia Mirhoseini:
An Architecture Search Framework for Inference-Time Techniques. ICML 2025- [i6]Jon Saad-Falcon, Estefany Kelly Buchanan, Mayee F. Chen, Tzu-Heng Huang, Brendan McLaughlin, Tanvir Bhathal, Shang Zhu, Ben Athiwaratkun, Frederic Sala, Scott W. Linderman, Azalia Mirhoseini, Christopher Ré:
Shrinking the Generation-Verification Gap with Weak Verifiers. CoRR abs/2506.18203 (2025) - [i5]Xavier Gonzalez, Estefany Kelly Buchanan, Hyun Dong Lee, Jerry Weihong Liu, Ke Alexander Wang, David M. Zoltowski, Christopher Ré, Scott W. Linderman:
A Unifying Framework for Parallelizing Sequential Models with Linear Dynamical Systems. CoRR abs/2509.21716 (2025) - 2024
- [b1]Estefany Kelly Buchanan:
Building reliable machine learning systems for neuroscience. Columbia University, USA, 2024 - [j2]Taiga Abe, Estefany Kelly Buchanan, Geoff Pleiss, John P. Cunningham:
Pathologies of Predictive Diversity in Deep Ensembles. Trans. Mach. Learn. Res. 2024 (2024) - [i4]Jon Saad-Falcon, Adrian Gamarra Lafuente, Shlok Natarajan, Nahum Maru, Hristo Todorov, Etash Kumar Guha, Estefany Kelly Buchanan, Mayee F. Chen, Neel Guha, Christopher Ré, Azalia Mirhoseini:
Archon: An Architecture Search Framework for Inference-Time Techniques. CoRR abs/2409.15254 (2024) - [i3]Francis R. Willett, Jingyuan Li, Trung Le, Chaofei Fan, Mingfei Chen, Eli Shlizerman, Yue Chen, Xin Zheng, Tatsuo S. Okubo, Tyler Benster, Hyun Dong Lee, Maxwell Kounga, Estefany Kelly Buchanan, David M. Zoltowski, Scott W. Linderman, Jaimie M. Henderson:
Brain-to-Text Benchmark '24: Lessons Learned. CoRR abs/2412.17227 (2024) - 2023
- [i2]Taiga Abe, Estefany Kelly Buchanan, Geoff Pleiss, John P. Cunningham:
Pathologies of Predictive Diversity in Deep Ensembles. CoRR abs/2302.00704 (2023) - 2022
- [c2]Taiga Abe, Estefany Kelly Buchanan, Geoff Pleiss, Richard S. Zemel, John P. Cunningham:
Deep Ensembles Work, But Are They Necessary? NeurIPS 2022 - [i1]Taiga Abe, Estefany Kelly Buchanan, Geoff Pleiss, Richard S. Zemel, John P. Cunningham:
Deep Ensembles Work, But Are They Necessary? CoRR abs/2202.06985 (2022) - 2021
- [j1]Matthew R. Whiteway
, Dan Biderman, Yoni Friedman, Mario Dipoppa, Estefany Kelly Buchanan, Anqi Wu, John Zhou, Niccolò Bonacchi, Nathaniel J. Miska, Jean-Paul Noel, Erica Rodriguez, Michael Schartner, Karolina Socha, Anne E. Urai, C. Daniel Salzman, International Brain Laboratory, John P. Cunningham, Liam Paninski:
Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders. PLoS Comput. Biol. 17(9) (2021) - 2020
- [c1]Anqi Wu, Estefany Kelly Buchanan, Matthew R. Whiteway, Michael Schartner, Guido Meijer, Jean-Paul Noel, Erica Rodriguez, Claire Everett, Amy Norovich, Evan Schaffer, Neeli Mishra, C. Daniel Salzman, Dora E. Angelaki, Andrés Bendesky, International Brain Laboratory, John P. Cunningham, Liam Paninski:
Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking. NeurIPS 2020
Coauthor Index
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