Sébastien Lachapelle
12 papers · 2020–2025 · 5 conferences · across top CS/AI conferences
Achievements
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🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌈 Renaissance Researcher (5) 🗺️ Taxonomy Completionist (16)
🌍
Conference Polyglot
(5)
🏃
Academic Marathon
(5)
🐝
Cross-Pollinator
(11)
💎
Century Club
(12)
🚀
Conference Pioneer
Conferences
ICLR (4)
AISTATS (2)
CLEAR (2)
ICML (2)
NIPS (2)
Top co-authors
Keywords
causal discovery
(3)
independent component analysis
(2)
disentangled representation
(2)
sparse learning
(1)
structure learning
(1)
continuous optimization
(1)
group lasso
(1)
sparse feature learning
(1)
convergence guarantee
(1)
latent variable
(1)
normalizing flow
(1)
variational autoencoder
(1)
object-centric learning
(1)
latent factor
(1)
interventional datum
(1)
directed acyclic graph
(1)
observational datum
(1)
causal graph
(1)
equivalence class
(1)
augmented lagrangian method
(1)
Papers
Interaction Asymmetry: A General Principle for Learning Composable Abstractions
ICLR 2025
All or None: Identifiable Linear Properties of Next-Token Predictors in Language Modeling
AISTATS 2025
Multi-View Causal Representation Learning with Partial Observability
ICLR 2024
A Sparsity Principle for Partially Observable Causal Representation Learning
ICML 2024
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation
NIPS 2023
Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning
ICML 2023
Typing assumptions improve identification in causal discovery
CLEAR 2022
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA
CLEAR 2022
On the Convergence of Continuous Constrained Optimization for Structure Learning
AISTATS 2022
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
ICLR 2020
Differentiable Causal Discovery from Interventional Data
NIPS 2020
Gradient-Based Neural DAG Learning
ICLR 2020