Alexandre Lacoste
28 papers · 2012–2025 · 10 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+13 more ↓ Show less ↑
π Conference Polyglot (10) π£ Hot Topic Early Bird π§ Keyword Pioneer π Interdisciplinary Bridge π Academic Marathon (13)
π
Interdisciplinary Bridge
πΊοΈ
Taxonomy Completionist
(50)
π£
Hot Topic Early Bird
π§¬
Topic Evolution
π
Triple Crown
π
Keyword Champion
ποΈ
Keyword Collector
(109)
β‘
Prolific Year
(5)
π
Conference Pioneer
π
Century Club
(28)
π₯
Unstoppable
(10)
π
Trend Setter
β
The Questioner
Conferences
NIPS (8)
ICML (6)
ICCV (3)
ACL (2)
AISTATS (2)
CLEAR (2)
ICLR (2)
ECCV (1)
EMNLP (1)
UAI (1)
Top co-authors
Keywords
variational autoencoder
(3)
variational inference
(2)
normalizing flow
(2)
object counting
(2)
remote sensing
(2)
causal discovery
(2)
self-supervised learning
(2)
autoregressive model
(2)
representation learning
(2)
reinforcement learning
(1)
semi-supervised learning
(1)
metric learning
(1)
few-shot learning
(1)
model selection
(1)
image classification
(1)
unsupervised learning
(1)
benchmark evaluation
(1)
independent component analysis
(1)
semantic segmentation
(1)
ensemble learning
(1)
Papers
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++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks
NIPS 2024
WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?
ICML 2024
Choreographer: Learning and Adapting Skills in Imagination
ICLR 2023
GEO-Bench: Toward Foundation Models for Earth Monitoring
NIPS 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
NIPS 2020
Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning
NIPS 2020
Embedding Propagation: Smoother Manifold for Few-Shot Classification
ECCV 2020
Synbols: Probing Learning Algorithms with Synthetic Datasets
NIPS 2020
Stochastic Neural Network with Kronecker Flow
AISTATS 2020
Probability Distillation: A Caveat and Alternatives
UAI 2019
Hierarchical Importance Weighted Autoencoders
ICML 2019
TADAM: Task dependent adaptive metric for improved few-shot learning
NIPS 2018
Neural Autoregressive Flows
ICML 2018
Improving Explorability in Variational Inference with Annealed Variational Objectives
NIPS 2018
Coarse-to-Fine Question Answering for Long Documents
ACL 2017
Accurate Supervised and Semi-Supervised Machine Reading for Long Documents
EMNLP 2017
PAC-Bayesian Theory Meets Bayesian Inference
NIPS 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