Sanyam Kapoor

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 20

Top Topics

Gaussian Process

Top Venues

Publications

Sanyam Kapoor, Nate Gruver, Manley Roberts, Katherine M. Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson
Large Language Models Must Be Taught to Know What They Don't Know. CoRR (2024)
Tim G. J. Rudner, Sanyam Kapoor, Shikai Qiu, Andrew Gordon Wilson
Function-Space Regularization in Neural Networks: A Probabilistic Perspective. ICML (2023)
Shikai Qiu, Tim G. J. Rudner, Sanyam Kapoor, Andrew Gordon Wilson
Should We Learn Most Likely Functions or Parameters? NeurIPS (2023)
Shikai Qiu, Tim G. J. Rudner, Sanyam Kapoor, Andrew Gordon Wilson
Should We Learn Most Likely Functions or Parameters? CoRR (2023)
Tim G. J. Rudner, Sanyam Kapoor, Shikai Qiu, Andrew Gordon Wilson
Function-Space Regularization in Neural Networks: A Probabilistic Perspective. CoRR (2023)
Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu, Yann LeCun, Andrew Gordon Wilson
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors. CoRR (2022)
Sanae Lotfi, Marc Finzi, Sanyam Kapoor, Andres Potapczynski, Micah Goldblum, Andrew Gordon Wilson
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization. NeurIPS (2022)
Sanae Lotfi, Marc Finzi, Sanyam Kapoor, Andres Potapczynski, Micah Goldblum, Andrew Gordon Wilson
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization. CoRR (2022)
Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu, Yann LeCun, Andrew G. Wilson
Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors. NeurIPS (2022)
Sanyam Kapoor, Wesley J. Maddox, Pavel Izmailov, Andrew Gordon Wilson
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification. NeurIPS (2022)
Sanyam Kapoor, Wesley J. Maddox, Pavel Izmailov, Andrew Gordon Wilson
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification. CoRR (2022)
Sanyam Kapoor, Theofanis Karaletsos, Thang D. Bui
Variational Auto-Regressive Gaussian Processes for Continual Learning. ICML (2021)
Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes. ICML (2021)
Wesley J. Maddox, Sanyam Kapoor, Andrew Gordon Wilson
When are Iterative Gaussian Processes Reliably Accurate? CoRR (2021)
Sanyam Kapoor, Valerio Perrone
A Simple and Fast Baseline for Tuning Large XGBoost Models. CoRR (2021)
Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes. CoRR (2021)
Sanyam Kapoor, Theofanis Karaletsos, Thang D. Bui
Variational Auto-Regressive Gaussian Processes for Continual Learning. CoRR (2020)
Ted Moskovitz, Rui Wang, Janice Lan, Sanyam Kapoor, Thomas Miconi, Jason Yosinski, Aditya Rawal
First-Order Preconditioning via Hypergradient Descent. CoRR (2019)
Cinjon Resnick, Roberta Raileanu, Sanyam Kapoor, Alex Peysakhovich, Kyunghyun Cho, Joan Bruna
Backplay: "Man muss immer umkehren". CoRR (2018)
Sanyam Kapoor
Multi-Agent Reinforcement Learning: A Report on Challenges and Approaches. CoRR (2018)