Simpson, Daniel

6 publications

ICLR 2025 Scalable Bayesian Learning with Posteriors Samuel Duffield, Kaelan Donatella, Johnathan Chiu, Phoebe Klett, Daniel Simpson

JMLR 2024 Pareto Smoothed Importance Sampling Aki Vehtari, Daniel Simpson, Andrew Gelman, Yuling Yao, Jonah Gabry

NeurIPSW 2023 Thermodynamic AI and Thermodynamic Linear Algebra Patrick J. Coles, Maxwell Aifer, Kaelan Donatella, Denis Melanson, Max Hunter Gordon, Thomas Dybdahl Ahle, Daniel Simpson, Gavin Crooks, Antonio J Martinez, Faris Mouti Sbahi

AISTATS 2020 Asynchronous Gibbs Sampling Alexander Terenin, Daniel Simpson, David Draper

NeurIPS 2020 Hamiltonian Monte Carlo Using an Adjoint-Differentiated Laplace Approximation: Bayesian Inference for Latent Gaussian Models and Beyond Charles Margossian, Aki Vehtari, Daniel Simpson, Raj Agrawal

ICML 2018 Yes, but Did It Work?: Evaluating Variational Inference Yuling Yao, Aki Vehtari, Daniel Simpson, Andrew Gelman