Diana Cai - RankMe

19 papers A* 6A 2Journal 9Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Batch, match, and patch: low-rank approximations for score-based variational inference. AISTATS Chirag Modi, Diana Cai, Lawrence K. Saul
2025	J	`jnl`	Fisher meets Feynman: score-based variational inference with a product of experts. CoRR Diana Cai, Robert M. Gower, David M. Blei, Lawrence K. Saul
2024	A*	`conf`	Batch and match: black-box variational inference with a score-based divergence. ICML Diana Cai, Chirag Modi, Loucas Pillaud-Vivien, Charles Margossian, Robert M. Gower, David M. Blei, Lawrence K. Saul
2024	J	`jnl`	Batch and match: black-box variational inference with a score-based divergence. CoRR Diana Cai, Chirag Modi, Loucas Pillaud-Vivien, Charles C. Margossian, Robert M. Gower, David M. Blei, Lawrence K. Saul
2024	J	`jnl`	Batch, match, and patch: low-rank approximations for score-based variational inference. CoRR Chirag Modi, Diana Cai, Lawrence K. Saul
2024	A*	`conf`	EigenVI: score-based variational inference with orthogonal function expansions. NeurIPS Diana Cai, Chirag Modi, Charles Margossian, Robert M. Gower, David M. Blei, Lawrence K. Saul
2024	J	`jnl`	EigenVI: score-based variational inference with orthogonal function expansions. CoRR Diana Cai, Chirag Modi, Charles C. Margossian, Robert M. Gower, David M. Blei, Lawrence K. Saul
2024	J	`jnl`	KD-BIRL: Kernel Density Bayesian Inverse Reinforcement Learning. Trans. Mach. Learn. Res. Aishwarya Mandyam, Didong Li, Andrew Jones, Diana Cai, Barbara E. Engelhardt
2023	J	`jnl`	Kernel Density Bayesian Inverse Reinforcement Learning. CoRR Aishwarya Mandyam, Didong Li, Diana Cai, Andrew Jones, Barbara E. Engelhardt
2023	—	`—`	Probabilistic Inference When the Model Is Wrong Diana Cai
2022	A*	`conf`	Multi-fidelity Monte Carlo: a pseudo-marginal approach. NeurIPS Diana Cai, Ryan P. Adams
2022	J	`jnl`	Multi-fidelity Monte Carlo: a pseudo-marginal approach. CoRR Diana Cai, Ryan P. Adams
2021	A	`conf`	Active multi-fidelity Bayesian online changepoint detection. UAI Gregory W. Gundersen, Diana Cai, Chuteng Zhou, Barbara E. Engelhardt, Ryan P. Adams
2021	J	`jnl`	Active multi-fidelity Bayesian online changepoint detection. CoRR Gregory W. Gundersen, Diana Cai, Chuteng Zhou, Barbara E. Engelhardt, Ryan P. Adams
2021	A*	`conf`	Finite mixture models do not reliably learn the number of components. ICML Diana Cai, Trevor Campbell, Tamara Broderick
2021	A*	`conf`	Slice Sampling Reparameterization Gradients. NeurIPS David M. Zoltowski, Diana Cai, Ryan P. Adams
2020	J	`jnl`	Weighted Meta-Learning. CoRR Diana Cai, Rishit Sheth, Lester Mackey, Nicoló Fusi
2018	A*	`conf`	A Bayesian Nonparametric View on Count-Min Sketch. NeurIPS Diana Cai, Michael Mitzenmacher, Ryan P. Adams
2016	—	`conf`	Edge-exchangeable graphs and sparsity. NIPS Diana Cai, Trevor Campbell, Tamara Broderick