Antoine Dedieu
12 papers · 2019–2025 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+5 more ↓ Show less ↑
🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (31)
🏆
Keyword Champion
(2)
🗃️
Keyword Collector
(76)
💎
Century Club · Bronze
🔥
Unstoppable · Bronze
🌈
Renaissance Researcher
(5)
Top co-authors
Research topics
Machine Learning
(10)
Artificial Intelligence
(9)
Core Methods
(8)
Optimization & Theory
(6)
Bayesian & Probabilistic · Artificial Intelligence
(5)
Deep Learning
(3)
Mathematics & Optimization
(3)
Core AI
(3)
Reinforcement Learning
(2)
Applications
(2)
Architectures
(2)
Bayesian & Probabilistic · Machine Learning
(2)
Learning Types
(2)
Optimization
(2)
Natural Language Processing
(1)
Keywords
sparse classifier
(2)
l0 regularization
(2)
probabilistic graphical model
(2)
l1 regularization
(2)
approximate inference
(2)
markov random field
(2)
sparse optimization
(2)
bayesian inference
(1)
variational inference
(1)
variable selection
(1)
sample complexity
(1)
transformer
(1)
ising model
(1)
in-context learning
(1)
feature selection
(1)
probabilistic modeling
(1)
column generation
(1)
loopy belief propagation
(1)
continuous control
(1)
belief propagation
(1)
Papers
Improving Transformer World Models for Data-Efficient RL
ICML 2025
DMC-VB: A Benchmark for Representation Learning for Control with Visual Distractors
NeurIPS 2024
Learning Cognitive Maps from Transformer Representations for Efficient Planning in Partially Observed Environments
ICML 2024
PGMax: Factor Graphs for Discrete Probabilistic Graphical Models and Loopy Belief Propagation in JAX
JMLR 2024
Learning Noisy OR Bayesian Networks with Max-Product Belief Propagation
ICML 2023
Schema-learning and rebinding as mechanisms of in-context learning and emergence
NeurIPS 2023
Solving L1-regularized SVMs and Related Linear Programs: Revisiting the Effectiveness of Column and Constraint Generation
JMLR 2022
Learning Sparse Classifiers: Continuous and Mixed Integer Optimization Perspectives
JMLR 2021
Perturb-and-max-product: Sampling and learning in discrete energy-based models
NeurIPS 2021
Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables
AAAI 2021
Sample-Efficient L0-L2 Constrained Structure Learning of Sparse Ising Models
AAAI 2021
Error bounds for sparse classifiers in high-dimensions
AISTATS 2019