Alexandre Drouin

Orcid: 0000-0001-7718-0319

According to our database1, Alexandre Drouin authored at least 33 papers between 2013 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Context is Key: A Benchmark for Forecasting with Essential Textual Information.
CoRR, 2024

Sample Compression Hypernetworks: From Generalization Bounds to Meta-Learning.
CoRR, 2024

Causal Representation Learning in Temporal Data via Single-Parent Decoding.
CoRR, 2024

InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation.
CoRR, 2024

WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks.
CoRR, 2024

Evaluating Interventional Reasoning Capabilities of Large Language Models.
CoRR, 2024

WorkArena: How Capable Are Web Agents at Solving Common Knowledge Work Tasks?
CoRR, 2024

WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?
Proceedings of the Forty-first International Conference on Machine Learning, 2024

TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Capture the Flag: Uncovering Data Insights with Large Language Models.
CoRR, 2023

Lag-Llama: Towards Foundation Models for Time Series Forecasting.
CoRR, 2023

Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation.
CoRR, 2023

Causal Discovery with Language Models as Imperfect Experts.
CoRR, 2023

Invariant Causal Set Covering Machines.
CoRR, 2023

GEO-Bench: Toward Foundation Models for Earth Monitoring.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Regions of Reliability in the Evaluation of Multivariate Probabilistic Forecasts.
Proceedings of the International Conference on Machine Learning, 2023

2022
RandomSCM: interpretable ensembles of sparse classifiers tailored for omics data.
CoRR, 2022

TACTiS: Transformer-Attentional Copulas for Time Series.
Proceedings of the International Conference on Machine Learning, 2022

Typing assumptions improve identification in causal discovery.
Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021
Toward Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark.
CoRR, 2021

byteSteady: Fast Classification Using Byte-Level n-Gram Embeddings.
CoRR, 2021

2020
Synbols: Probing Learning Algorithms with Synthetic Datasets.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

In search of robust measures of generalization.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Differentiable Causal Discovery from Interventional Data.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Embedding Propagation: Smoother Manifold for Few-Shot Classification.
Proceedings of the Computer Vision - ECCV 2020, 2020

Phylogenetic Manifold Regularization: A semi-supervised approach to predict transcription factor binding sites.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

2018
Deep Learning for Electromyographic Hand Gesture Signal Classification by Leveraging Transfer Learning.
CoRR, 2018

2017
Maximum Margin Interval Trees.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Large scale modeling of antimicrobial resistance with interpretable classifiers.
CoRR, 2016

2015
Greedy Biomarker Discovery in the Genome with Applications to Antimicrobial Resistance.
CoRR, 2015

2014
Learning interpretable models of phenotypes from whole genome sequences with the Set Covering Machine.
CoRR, 2014

2013
Learning a peptide-protein binding affinity predictor with kernel ridge regression.
BMC Bioinform., 2013

Accelerated Robust Point Cloud Registration in Natural Environments through Positive and Unlabeled Learning.
Proceedings of the IJCAI 2013, 2013


  Loading...