Sanyam Kapoor - RankMe

25 papers A* 9Journal 15Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Compute-Optimal LLMs Provably Generalize Better With Scale. CoRR Marc Finzi, Sanyam Kapoor, Diego Granziol, Anming Gu, Christopher De Sa, J. Zico Kolter, Andrew Gordon Wilson
2025	A*	`conf`	Compute-Optimal LLMs Provably Generalize Better with Scale. ICLR Marc Anton Finzi, Sanyam Kapoor, Diego Granziol, Anming Gu, Christopher De Sa, J. Zico Kolter, Andrew Gordon Wilson
2025	J	`jnl`	When Should We Orchestrate Multiple Agents? CoRR Umang Bhatt, Sanyam Kapoor, Mihir Upadhyay, Ilia Sucholutsky, Francesco Quinzan, Katherine M. Collins, Adrian Weller, Andrew Gordon Wilson, Muhammad Bilal Zafar
2024	A*	`conf`	Large Language Models Must Be Taught to Know What They Don't Know. NeurIPS Sanyam Kapoor, Nate Gruver, Manley Roberts, Katie Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson
2024	J	`jnl`	Large Language Models Must Be Taught to Know What They Don't Know. CoRR Sanyam Kapoor, Nate Gruver, Manley Roberts, Katherine M. Collins, Arka Pal, Umang Bhatt, Adrian Weller, Samuel Dooley, Micah Goldblum, Andrew Gordon Wilson
2024	—	`conf`	Uncertainty Quantification for Conditional Treatment Effect Estimation under Dynamic Treatment Regimes. ML4H@NeurIPS Leon Deng, Hong Xiong, Feng Wu, Sanyam Kapoor, Soumya Gosh, Zach Shahn, Li-Wei H. Lehman
2023	A*	`conf`	Function-Space Regularization in Neural Networks: A Probabilistic Perspective. ICML Tim G. J. Rudner, Sanyam Kapoor, Shikai Qiu, Andrew Gordon Wilson
2023	J	`jnl`	Function-Space Regularization in Neural Networks: A Probabilistic Perspective. CoRR Tim G. J. Rudner, Sanyam Kapoor, Shikai Qiu, Andrew Gordon Wilson
2023	A*	`conf`	Should We Learn Most Likely Functions or Parameters? NeurIPS Shikai Qiu, Tim G. J. Rudner, Sanyam Kapoor, Andrew Gordon Wilson
2023	J	`jnl`	Should We Learn Most Likely Functions or Parameters? CoRR Shikai Qiu, Tim G. J. Rudner, Sanyam Kapoor, Andrew Gordon Wilson
2022	A*	`conf`	On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification. NeurIPS Sanyam Kapoor, Wesley J. Maddox, Pavel Izmailov, Andrew Gordon Wilson
2022	J	`jnl`	On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification. CoRR Sanyam Kapoor, Wesley J. Maddox, Pavel Izmailov, Andrew Gordon Wilson
2022	A*	`conf`	PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization. NeurIPS Sanae Lotfi, Marc Finzi, Sanyam Kapoor, Andres Potapczynski, Micah Goldblum, Andrew Gordon Wilson
2022	J	`jnl`	PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization. CoRR Sanae Lotfi, Marc Finzi, Sanyam Kapoor, Andres Potapczynski, Micah Goldblum, Andrew Gordon Wilson
2022	A*	`conf`	Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors. NeurIPS Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu, Yann LeCun, Andrew Gordon Wilson
2022	J	`jnl`	Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priors. CoRR Ravid Shwartz-Ziv, Micah Goldblum, Hossein Souri, Sanyam Kapoor, Chen Zhu, Yann LeCun, Andrew Gordon Wilson
2021	J	`jnl`	A Simple and Fast Baseline for Tuning Large XGBoost Models. CoRR Sanyam Kapoor, Valerio Perrone
2021	A*	`conf`	SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes. ICML Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
2021	J	`jnl`	SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes. CoRR Sanyam Kapoor, Marc Finzi, Ke Alexander Wang, Andrew Gordon Wilson
2021	A*	`conf`	Variational Auto-Regressive Gaussian Processes for Continual Learning. ICML Sanyam Kapoor, Theofanis Karaletsos, Thang D. Bui
2021	J	`jnl`	When are Iterative Gaussian Processes Reliably Accurate? CoRR Wesley J. Maddox, Sanyam Kapoor, Andrew Gordon Wilson
2020	J	`jnl`	Variational Auto-Regressive Gaussian Processes for Continual Learning. CoRR Sanyam Kapoor, Theofanis Karaletsos, Thang D. Bui
2019	J	`jnl`	First-Order Preconditioning via Hypergradient Descent. CoRR Ted Moskovitz, Rui Wang, Janice Lan, Sanyam Kapoor, Thomas Miconi, Jason Yosinski, Aditya Rawal
2018	J	`jnl`	Backplay: "Man muss immer umkehren". CoRR Cinjon Resnick, Roberta Raileanu, Sanyam Kapoor, Alex Peysakhovich, Kyunghyun Cho, Joan Bruna
2018	J	`jnl`	Multi-Agent Reinforcement Learning: A Report on Challenges and Approaches. CoRR Sanyam Kapoor