Estefany Kelly Buchanan

According to our database, Estefany Kelly Buchanan authored at least 15 papers between 2020 and 2026.

Collaborative distances:

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

2026

Test-Time Scaling Makes Overtraining Compute-Optimal.

Nicholas Carl Roberts, Sungjun Cho, Zhiqi Gao, Tzu-Heng Huang, Albert Wu, Gabriel Orlanski, Avi Trost, Estefany Kelly Buchanan, Aws Albarghouthi, Frederic Sala

CoRR, April, 2026

Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces.

Mike A. Merrill, Alexander Glenn Shaw, Nicholas Carlini, Boxuan Li, Harsh Raj, Ivan Bercovich, Lin Shi, Jeong Yeon Shin, Thomas Walshe, Estefany Kelly Buchanan, Junhong Shen, Guanghao Ye, Haowei Lin, Jason Poulos, Maoyu Wang, Marianna Nezhurina, Jenia Jitsev, Di Lu, Orfeas Menis-Mastromichalakis, Zhiwei Xu, Zizhao Chen, Yue Liu, Robert Zhang, Leon Liangyu Chen, Anurag Kashyap, Jan-Lucas Uslu, Jeffrey Li, Jianbo Wu, Minghao Yan, Song Bian, Vedang Sharma, Ke Sun, Steven Dillmann, Akshay Anand, Andrew Lanpouthakoun, Bardia Koopah, Changran Hu, Etash Kumar Guha, Gabriel H. S. Dreiman, Jiacheng Zhu, Karl Krauth, Li Zhong, Niklas Muennighoff, Robert Amanfu, Shangyin Tan, Shreyas Pimpalgaonkar, Tushar Aggarwal, Xiangning Lin, Xin Lan, Xuandong Zhao, Yiqing Liang, Yuanli Wang, Zilong Wang, Changzhi Zhou, David Heineman, Hange Liu, Harsh Trivedi, John Yang, Junhong Lin, Manish Shetty, Michael Yang, Nabil Omi, Negin Raoof, Shanda Li, Terry Yue Zhuo, Wuwei Lin, Yiwei Dai, Yuxin Wang, Wenhao Chai, Shang Zhou, Dariush Wahdany, Ziyu She, Jiaming Hu, Zhikang Dong, Yuxuan Zhu, Sasha Cui, Ahson Saiyed, Arinbjörn Kolbeinsson, Jesse Hu, Christopher Michael Rytting, Ryan Marten, Yixin Wang, Alex Dimakis, Andy Konwinski, Ludwig Schmidt

CoRR, January, 2026

A Unifying Framework for Parallelizing Sequential Models with Linear Dynamical Systems.

Xavier Gonzalez, Estefany Kelly Buchanan, Hyun Dong Lee, Jerry Weihong Liu, Ke Alexander Wang, David M. Zoltowski, Leo Kozachkov, Christopher Ré, Scott W. Linderman

Trans. Mach. Learn. Res., 2026

2025

A Unifying Framework for Parallelizing Sequential Models with Linear Dynamical Systems.

Xavier Gonzalez, Estefany Kelly Buchanan, Hyun Dong Lee, Jerry Weihong Liu, Ke Alexander Wang, David M. Zoltowski, Christopher Ré, Scott W. Linderman

CoRR, September, 2025

Shrinking the Generation-Verification Gap with Weak Verifiers.

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

CoRR, June, 2025

Weaver: Shrinking the Generation-Verification Gap by Scaling Compute for Verification.

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

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Extracting task-relevant preserved dynamics from contrastive aligned neural recordings.

Yiqi Jiang, Kaiwen Sheng, Yujia Gao, Estefany Kelly Buchanan, Yu Shikano, Seung Je Woo, Yixiu Zhao, Tony Hyun Kim, Fatih Dinc, Scott W. Linderman, Mark J. Schnitzer

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

An Architecture Search Framework for Inference-Time Techniques.

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

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Building reliable machine learning systems for neuroscience

Estefany Kelly Buchanan

PhD thesis, 2024

Pathologies of Predictive Diversity in Deep Ensembles.

Taiga Abe, Estefany Kelly Buchanan, Geoff Pleiss, John P. Cunningham

Trans. Mach. Learn. Res., 2024

Brain-to-Text Benchmark '24: Lessons Learned.

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

CoRR, 2024

Archon: An Architecture Search Framework for Inference-Time Techniques.

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

CoRR, 2024

2022

Deep Ensembles Work, But Are They Necessary?

Taiga Abe, Estefany Kelly Buchanan, Geoff Pleiss, Richard S. Zemel, John P. Cunningham

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders.

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

PLoS Comput. Biol., 2021

2020

Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking.

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020