Debiased Bayesian inference for average treatment effects. - Kolyan Ray; Botond Szabó (NeurIPS, 2019)

Spike and slab variational Bayes for high dimensional logistic regression. - Kolyan Ray; Botond Szabó; Gabriel Clara (NeurIPS, 2020)

Nonparametric Bayesian inference for reversible multi-dimensional diffusions. - Matteo Giordano; Kolyan Ray (CoRR, 2020)

On the inability of Gaussian process regression to optimally learn compositional functions. - Matteo Giordano; Kolyan Ray; Johannes Schmidt-Hieber (NeurIPS, 2022)

Variational Bayes for high-dimensional proportional hazards models with applications within gene expression. - Michael Komodromos; Eric O. Aboagye; Marina Evangelou; Sarah Filippi; Kolyan Ray (Bioinform., 2022)

Pointwise uncertainty quantification for sparse variational Gaussian process regression with a Brownian motion prior. - Luke Travis; Kolyan Ray (NeurIPS, 2023)

Semiparametric Inference Using Fractional Posteriors. - Alice L'Huillier; Luke Travis; Ismaël Castillo; Kolyan Ray (J. Mach. Learn. Res., 2023)

Bayesian Nonparametric Inference in McKean-Vlasov models. - Richard Nickl; Grigorios A. Pavliotis; Kolyan Ray (CoRR, 2024)

A variational Bayes approach to debiased inference for low-dimensional parameters in high-dimensional linear regression. - Ismaël Castillo; Alice L'Huillier; Kolyan Ray; Luke Travis (CoRR, 2024)