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07/11/2023
Metropolis Sampling for Constrained Diffusion Models
Denoising diffusion models have recently emerged as the predominant para...
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04/11/2023
Diffusion Models for Constrained Domains
Denoising diffusion models are a recent class of generative models which...
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09/28/2022
Spectral Diffusion Processes
Score-based generative modelling (SGM) has proven to be a very effective...
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07/07/2022
Riemannian Diffusion Schrödinger Bridge
Score-based generative models exhibit state of the art performance on de...
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02/06/2022
Riemannian Score-Based Generative Modeling
Score-based generative models (SGMs) are a novel class of generative mod...
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10/27/2021
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels
Gaussian processes are machine learning models capable of learning unkno...
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01/07/2021
Enhanced Direct Delta Mush
Direct Delta Mush is a novel skinning deformation technique introduced b...
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12/20/2020
LieTransformer: Equivariant self-attention for Lie Groups
Group equivariant neural networks are used as building blocks of group i...
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11/25/2020
Equivariant Conditional Neural Processes
We introduce Equivariant Conditional Neural Processes (EquivCNPs), a new...
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11/24/2019