Emile Mathieu
13 papers · 2019–2024 · 3 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Bronze 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (22)
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Topic Evolution
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Century Club · Bronze
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Unstoppable · Bronze
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Prolific Year · Productive
Venues
Top co-authors
Research topics
Deep Learning
(11)
Machine Learning
(10)
Models
(10)
Core Methods
(6)
Learning Types · Deep Learning
(4)
Learning Types · Machine Learning
(4)
Artificial Intelligence
(2)
Architectures
(2)
Bayesian & Probabilistic
(2)
Optimization & Theory
(2)
Computer Vision
(1)
Healthcare & Medicine
(1)
Mathematics & Optimization
(1)
Application Areas
(1)
Generation
(1)
Keywords
diffusion model
(6)
representation learning
(3)
variational autoencoder
(3)
riemannian manifold
(3)
generative model
(3)
conditional generation
(2)
normalizing flow
(2)
data augmentation
(1)
constrained generation
(1)
manifold learning
(1)
hierarchical representation
(1)
probability distribution
(1)
stochastic process
(1)
score matching
(1)
importance sampling
(1)
time series
(1)
self-supervised learning
(1)
probability measure
(1)
latent representation
(1)
image reconstruction
(1)
Papers
DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised h-transform
NeurIPS 2024
On conditional diffusion models for PDE simulations
NeurIPS 2024
Geometric Neural Diffusion Processes
NeurIPS 2023
Learning Instance-Specific Augmentations by Capturing Local Invariances
ICML 2023
Metropolis Sampling for Constrained Diffusion Models
NeurIPS 2023
SE(3) diffusion model with application to protein backbone generation
ICML 2023
SE(3) Equivariant Augmented Coupling Flows
NeurIPS 2023
On Incorporating Inductive Biases into VAEs
ICLR 2022
Riemannian Score-Based Generative Modelling
NeurIPS 2022
On Contrastive Representations of Stochastic Processes
NeurIPS 2021
Riemannian Continuous Normalizing Flows
NeurIPS 2020
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders
NeurIPS 2019
Disentangling Disentanglement in Variational Autoencoders
ICML 2019