Alexandre Lacoste
29 papers · 2012–2026 · 11 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (56) 🏃 Academic Marathon · Half 🌍 Conference Polyglot · Gold 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
🏆
Keyword Champion
🧬
Topic Evolution
👑
Triple Crown
🌈
Renaissance Researcher
(7)
🔥
Unstoppable · Silver
❓
The Questioner
⚡
Prolific Year · Productive
🚀
Conference Pioneer
💎
Century Club · Bronze
📈
Trend Setter
🗃️
Keyword Collector
(130)
Venues
Top co-authors
Research topics
Machine Learning
(20)
Artificial Intelligence
(16)
Core AI
(13)
Deep Learning
(11)
Learning Types · Machine Learning
(10)
Models
(7)
Optimization & Theory
(6)
Core Methods
(5)
Computer Vision
(4)
Application Areas
(4)
Learning Types · Deep Learning
(4)
Domain-Specific
(3)
Learning Paradigms
(3)
Techniques
(3)
Natural Language Processing
(2)
Keywords
variational autoencoder
(4)
representation learning
(3)
causal discovery
(2)
causal graphical model
(2)
remote sensing
(2)
variational inference
(2)
object counting
(2)
self-supervised learning
(2)
normalizing flow
(2)
autoregressive model
(2)
mechanism sparsity
(2)
model-based reinforcement learning
(2)
model selection
(1)
few-shot learning
(1)
reinforcement learning
(1)
semi-supervised learning
(1)
metric learning
(1)
image classification
(1)
unsupervised learning
(1)
benchmark evaluation
(1)
Papers
Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies
JMLR 2026
Context is Key: A Benchmark for Forecasting with Essential Textual Information
ICML 2025
GEOBench-VLM: Benchmarking Vision-Language Models for Geospatial Tasks
ICCV 2025
InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation
ICLR 2025
WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?
ICML 2024
WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks
NeurIPS 2024
Choreographer: Learning and Adapting Skills in Imagination
ICLR 2023
GEO-Bench: Toward Foundation Models for Earth Monitoring
NeurIPS 2023
Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels
ICML 2023
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA
CLeaR 2022
Typing assumptions improve identification in causal discovery
CLeaR 2022
Beyond Trivial Counterfactual Explanations With Diverse Valuable Explanations
ICCV 2021
Seasonal Contrast: Unsupervised Pre-Training From Uncurated Remote Sensing Data
ICCV 2021
Differentiable Causal Discovery from Interventional Data
NeurIPS 2020
Embedding Propagation: Smoother Manifold for Few-Shot Classification
ECCV 2020
Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning
NeurIPS 2020
Stochastic Neural Network with Kronecker Flow
AISTATS 2020
Synbols: Probing Learning Algorithms with Synthetic Datasets
NeurIPS 2020
Hierarchical Importance Weighted Autoencoders
ICML 2019
Probability Distillation: A Caveat and Alternatives
UAI 2019
Improving Explorability in Variational Inference with Annealed Variational Objectives
NeurIPS 2018
Neural Autoregressive Flows
ICML 2018
TADAM: Task dependent adaptive metric for improved few-shot learning
NeurIPS 2018
Accurate Supervised and Semi-Supervised Machine Reading for Long Documents
EMNLP 2017
Coarse-to-Fine Question Answering for Long Documents
ACL 2017
PAC-Bayesian Theory Meets Bayesian Inference
NeurIPS 2016
WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia
ACL 2016
Agnostic Bayesian Learning of Ensembles
ICML 2014
Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets
AISTATS 2012