Huggins, Jonathan H.

6 publications

UAI 2025 Tuning-Free Coreset Markov Chain Monte Carlo via Hot DoG Naitong Chen, Jonathan H. Huggins, Trevor Campbell

JMLR 2024 A Framework for Improving the Reliability of Black-Box Variational Inference Manushi Welandawe, Michael Riis Andersen, Aki Vehtari, Jonathan H. Huggins

AISTATS 2023 A Targeted Accuracy Diagnostic for Variational Approximations Yu Wang, Mikolaj Kasprzak, Jonathan H. Huggins

ICMLW 2021 Challenges for BBVI with Normalizing Flows Akash Kumar Dhaka, Alejandro Catalina, Manushi Welandawe, Michael Riis Andersen, Jonathan H. Huggins, Aki Vehtari

NeurIPSW 2020 Independent Versus Truncated Finite Approximations for Bayesian Nonparametric Inference Tin D. Nguyen, Jonathan H. Huggins, Lorenzo Masoero, Lester Mackey, Tamara Broderick

AISTATS 2019 Scalable Gaussian Process Inference with Finite-Data Mean and Variance Guarantees Jonathan H. Huggins, Trevor Campbell, Mikolaj Kasprzak, Tamara Broderick