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08/20/2023
SE(3) Equivariant Augmented Coupling Flows
Coupling normalizing flows allow for fast sampling and density evaluatio...
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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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07/11/2023
Geometric Neural Diffusion Processes
Denoising diffusion models have proven to be a flexible and effective pa...
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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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02/05/2023
SE(3) diffusion model with application to protein backbone generation
The design of novel protein structures remains a challenge in protein en...
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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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06/25/2021
InteL-VAEs: Adding Inductive Biases to Variational Auto-Encoders via Intermediary Latents
We introduce a simple and effective method for learning VAEs with contro...
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06/18/2021
On Contrastive Representations of Stochastic Processes
Learning representations of stochastic processes is an emerging problem ...
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06/18/2020
Riemannian Continuous Normalizing Flows
Normalizing flows have shown great promise for modelling flexible probab...
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01/17/2019
Hierarchical Representations with Poincaré Variational Auto-Encoders
The Variational Auto-Encoder (VAE) model has become widely popular as a ...
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12/06/2018
Disentangling Disentanglement
We develop a generalised notion of disentanglement in Variational Auto-E...
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07/09/2018
