Diana Cai

According to our database, Diana Cai authored at least 16 papers between 2016 and 2025.

Collaborative distances:

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

2025

Fisher meets Feynman: score-based variational inference with a product of experts.

Diana Cai, Robert M. Gower, David M. Blei, Lawrence K. Saul

CoRR, October, 2025

Reconstruction of δ13CDIC in the Atlantic Ocean: A Probabilistic Machine Learning Approach for Filling Historical Data Gaps.

Hui Gao, Zelun Wu, Zhentao Sun, Diana Cai, Meibing Jin, Wei-Jun Cai

Dataset, August, 2025

Reconstruction of δ¹³CDIC in the Atlantic Ocean.

Hui Gao, Zelun Wu, Zhentao Sun, Diana Cai, Meibing Jin, Wei-Jun Cai

Dataset, July, 2025

Batch, match, and patch: low-rank approximations for score-based variational inference.

Chirag Modi, Diana Cai, Lawrence K. Saul

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

KD-BIRL: Kernel Density Bayesian Inverse Reinforcement Learning.

Aishwarya Mandyam, Didong Li, Andrew Jones, Diana Cai, Barbara E. Engelhardt

Trans. Mach. Learn. Res., 2024

EigenVI: score-based variational inference with orthogonal function expansions.

Diana Cai, Chirag Modi, Charles Margossian, Robert M. Gower, David M. Blei, Lawrence K. Saul

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Batch and match: black-box variational inference with a score-based divergence.

Diana Cai, Chirag Modi, Loucas Pillaud-Vivien, Charles Margossian, Robert M. Gower, David M. Blei, Lawrence K. Saul

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Probabilistic Inference When the Model Is Wrong

Diana Cai

PhD thesis, 2023

Kernel Density Bayesian Inverse Reinforcement Learning.

Aishwarya Mandyam, Didong Li, Diana Cai, Andrew Jones, Barbara E. Engelhardt

CoRR, 2023

2022

Multi-fidelity Monte Carlo: a pseudo-marginal approach.

Diana Cai, Ryan P. Adams

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

2021

Active multi-fidelity Bayesian online changepoint detection.

Gregory W. Gundersen, Diana Cai, Chuteng Zhou, Barbara E. Engelhardt, Ryan P. Adams

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Slice Sampling Reparameterization Gradients.

David M. Zoltowski, Diana Cai, Ryan P. Adams

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Finite mixture models do not reliably learn the number of components.

Diana Cai, Trevor Campbell, Tamara Broderick

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Weighted Meta-Learning.

Diana Cai, Rishit Sheth, Lester Mackey, Nicoló Fusi

CoRR, 2020

2018

A Bayesian Nonparametric View on Count-Min Sketch.

Diana Cai, Michael Mitzenmacher, Ryan P. Adams

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016

Edge-exchangeable graphs and sparsity.

Diana Cai, Trevor Campbell, Tamara Broderick

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016