Javier Antoran
10 papers · 2020–2024 · 3 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (21) 🤝 Dynamic Duo (10)
💎
Century Club · Bronze
📈
Trend Setter
🔥
Unstoppable · Bronze
Venues
Top co-authors
Research topics
Machine Learning
(9)
Optimization & Theory · Machine Learning
(8)
Artificial Intelligence
(4)
Deep Learning
(4)
Bayesian & Probabilistic · Artificial Intelligence
(4)
Core Methods
(4)
Bayesian & Probabilistic · Machine Learning
(3)
Models
(3)
Optimization & Theory · Deep Learning
(2)
Mathematics & Optimization
(1)
Application Areas
(1)
Architectures
(1)
Core AI
(1)
Learning Types · Machine Learning
(1)
Learning Types · Deep Learning
(1)
Keywords
gaussian process
(3)
uncertainty quantification
(3)
laplace approximation
(2)
uncertainty estimation
(2)
bayesian inference
(2)
stochastic gradient descent
(2)
bayesian deep learning
(2)
predictive uncertainty
(2)
model uncertainty
(2)
posterior sampling
(1)
importance sampling
(1)
data augmentation
(1)
probabilistic reasoning
(1)
conjugate gradient
(1)
normalizing flow
(1)
generative model
(1)
model evidence
(1)
marginal likelihood
(1)
posterior approximation
(1)
bayesian optimization
(1)
Papers
A Generative Model of Symmetry Transformations
NeurIPS 2024
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes
NeurIPS 2024
Stochastic Gradient Descent for Gaussian Processes Done Right
ICLR 2024
Sampling-based inference for large linear models, with application to linearised Laplace
ICLR 2023
Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent
NeurIPS 2023
SE(3) Equivariant Augmented Coupling Flows
NeurIPS 2023
Adapting the Linearised Laplace Model Evidence for Modern Deep Learning
ICML 2022
Bayesian Deep Learning via Subnetwork Inference
ICML 2021
Getting a CLUE: A Method for Explaining Uncertainty Estimates
ICLR 2021
Depth Uncertainty in Neural Networks
NeurIPS 2020