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ORCIDMichael J. Hutchinson
Person information
- affiliation: Google DeepMind
- affiliation: University of Oxford, Department of Statistics, UK
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2020 – today
- 2024
[c7]Angus Phillips, Hai-Dang Dau, Michael John Hutchinson, Valentin De Bortoli, George Deligiannidis, Arnaud Doucet:
Particle Denoising Diffusion Sampler. ICML 2024- [i13]Angus Phillips, Hai-Dang Dau, Michael John Hutchinson, Valentin De Bortoli, George Deligiannidis
, Arnaud Doucet:
Particle Denoising Diffusion Sampler. CoRR abs/2402.06320 (2024) - [i12]Valentin De Bortoli, Michael J. Hutchinson, Peter Wirnsberger, Arnaud Doucet:
Target Score Matching. CoRR abs/2402.08667 (2024) - [i11]Peter Mostowsky, Vincent Dutordoir, Iskander Azangulov, Noémie Jaquier, Michael John Hutchinson, Aditya Ravuri, Leonel Rozo, Alexander Terenin, Viacheslav Borovitskiy:
The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs. CoRR abs/2407.08086 (2024) - 2023
- [j1]Nic Fishman, Leo Klarner, Valentin De Bortoli, Emile Mathieu, Michael John Hutchinson:
Diffusion Models for Constrained Domains. Trans. Mach. Learn. Res. 2023 (2023) - [c6]Nic Fishman, Leo Klarner, Emile Mathieu, Michael J. Hutchinson, Valentin De Bortoli:
Metropolis Sampling for Constrained Diffusion Models. NeurIPS 2023 - [c5]Emile Mathieu, Vincent Dutordoir, Michael J. Hutchinson, Valentin De Bortoli, Yee Whye Teh, Richard E. Turner:
Geometric Neural Diffusion Processes. NeurIPS 2023 - [i10]Nic Fishman, Leo Klarner, Valentin De Bortoli, Emile Mathieu, Michael J. Hutchinson:
Diffusion Models for Constrained Domains. CoRR abs/2304.05364 (2023) - [i9]Emile Mathieu, Vincent Dutordoir, Michael J. Hutchinson, Valentin De Bortoli, Yee Whye Teh, Richard E. Turner:
Geometric Neural Diffusion Processes. CoRR abs/2307.05431 (2023) - [i8]Nic Fishman, Leo Klarner, Emile Mathieu, Michael J. Hutchinson, Valentin De Bortoli:
Metropolis Sampling for Constrained Diffusion Models. CoRR abs/2307.05439 (2023) - 2022
- [c4]Valentin De Bortoli, Emile Mathieu, Michael J. Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet:
Riemannian Score-Based Generative Modelling. NeurIPS 2022 - [i7]Valentin De Bortoli, Emile Mathieu, Michael J. Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet:
Riemannian Score-Based Generative Modeling. CoRR abs/2202.02763 (2022) - [i6]James Thornton, Michael J. Hutchinson, Emile Mathieu, Valentin De Bortoli, Yee Whye Teh, Arnaud Doucet:
Riemannian Diffusion Schrödinger Bridge. CoRR abs/2207.03024 (2022) - [i5]Angus Phillips, Thomas Seror, Michael J. Hutchinson, Valentin De Bortoli, Arnaud Doucet, Emile Mathieu:
Spectral Diffusion Processes. CoRR abs/2209.14125 (2022) - 2021
- [c3]Peter Holderrieth, Michael J. Hutchinson, Yee Whye Teh:
Equivariant Learning of Stochastic Fields: Gaussian Processes and Steerable Conditional Neural Processes. ICML 2021: 4297-4307 - [c2]Michael J. Hutchinson, Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee Whye Teh, Hyunjik Kim:
LieTransformer: Equivariant Self-Attention for Lie Groups. ICML 2021: 4533-4543 - [c1]Michael J. Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee Whye Teh, Marc Peter Deisenroth:
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels. NeurIPS 2021: 17160-17169 - [i4]Michael J. Hutchinson, Alexander Terenin, Viacheslav Borovitskiy, So Takao, Yee Whye Teh, Marc Peter Deisenroth:
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Equivariant Projected Kernels. CoRR abs/2110.14423 (2021) - 2020
- [i3]Peter Holderrieth, Michael J. Hutchinson, Yee Whye Teh:
Equivariant Conditional Neural Processes. CoRR abs/2011.12916 (2020) - [i2]Michael J. Hutchinson, Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee Whye Teh, Hyunjik Kim:
LieTransformer: Equivariant self-attention for Lie Groups. CoRR abs/2012.10885 (2020)
2010 – 2019
- 2019
- [i1]Mrinank Sharma, Michael J. Hutchinson, Siddharth Swaroop, Antti Honkela, Richard E. Turner:
Differentially Private Federated Variational Inference. CoRR abs/1911.10563 (2019)
Coauthor Index
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