Differentially Private Federated Variational Inference. - Mrinank Sharma; Michael J. Hutchinson; Siddharth Swaroop; Antti Honkela; Richard E. Turner (CoRR, 2019)

Equivariant Conditional Neural Processes. - Peter Holderrieth; Michael J. Hutchinson; Yee Whye Teh (CoRR, 2020)

Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes. - Peter Holderrieth; Michael J. Hutchinson; Yee Whye Teh (ICML, 2021)

LieTransformer: Equivariant Self-Attention for Lie Groups. - Michael J. Hutchinson; Charline Le Lan; Sheheryar Zaidi; Emilien Dupont; Yee Whye Teh; Hyunjik Kim (ICML, 2021)

Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels. - Michael J. Hutchinson; Alexander Terenin; Viacheslav Borovitskiy; So Takao; Yee Whye Teh; Marc Peter Deisenroth (NeurIPS, 2021)

Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Equivariant Projected Kernels. - Michael J. Hutchinson; Alexander Terenin; Viacheslav Borovitskiy; So Takao; Yee Whye Teh; Marc Peter Deisenroth (CoRR, 2021)

Riemannian Score-Based Generative Modelling. - Valentin De Bortoli; Emile Mathieu; Michael J. Hutchinson; James Thornton; Yee Whye Teh; Arnaud Doucet (NeurIPS, 2022)

Riemannian Score-Based Generative Modeling. - Valentin De Bortoli; Emile Mathieu; Michael J. Hutchinson; James Thornton; Yee Whye Teh; Arnaud Doucet (CoRR, 2022)

Riemannian Diffusion Schrödinger Bridge. - James Thornton; Michael J. Hutchinson; Emile Mathieu; Valentin De Bortoli; Yee Whye Teh; Arnaud Doucet (CoRR, 2022)

Spectral Diffusion Processes. - Angus Phillips; Thomas Seror; Michael J. Hutchinson; Valentin De Bortoli; Arnaud Doucet; Emile Mathieu (CoRR, 2022)

Metropolis Sampling for Constrained Diffusion Models. - Nic Fishman; Leo Klarner; Emile Mathieu; Michael J. Hutchinson; Valentin De Bortoli (NeurIPS, 2023)

Geometric Neural Diffusion Processes. - Emile Mathieu; Vincent Dutordoir; Michael J. Hutchinson; Valentin De Bortoli; Yee Whye Teh; Richard E. Turner (NeurIPS, 2023)

Diffusion Models for Constrained Domains. - Nic Fishman; Leo Klarner; Valentin De Bortoli; Emile Mathieu; Michael John Hutchinson (Trans. Mach. Learn. Res., 2023)

Particle Denoising Diffusion Sampler. - Angus Phillips; Hai-Dang Dau; Michael John Hutchinson; Valentin De Bortoli; George Deligiannidis; Arnaud Doucet (ICML, 2024)

Target Score Matching. - Valentin De Bortoli; Michael J. Hutchinson; Peter Wirnsberger; Arnaud Doucet (CoRR, 2024)

The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs. - Peter Mostowsky; Vincent Dutordoir; Iskander Azangulov; Noémie Jaquier; Michael John Hutchinson; Aditya Ravuri; Leonel Rozo; Alexander Terenin; Viacheslav Borovitskiy (CoRR, 2024)