← Authors

Hugo Larochelle

54 papers · 2006–2025 · 9 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (9) πŸ—ΊοΈ Taxonomy Completionist (25) πŸƒ Academic Marathon (19) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (13) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🌟 Keyword Trendsetter Combo (13) πŸ† Keyword Champion πŸ‘‘ Triple Crown 🌱 Topic Pioneer 🧬 Topic Evolution 🀝 Dynamic Duo (10) πŸ† Grand Slam πŸ”¬ Deep Specialist (14) ❓ The Questioner πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (17) ⚑ Prolific Year (9) πŸ—ƒοΈ Keyword Collector (60) πŸ’Ž Century Club (54)

Conferences

NIPS (15) ICLR (10) ICML (10) JMLR (8) AISTATS (3) CVPR (3) AAAI (2) ICCV (2) IJCAI (1)

Top co-authors

Yoshua Bengio (10) Daniel Tarlow (5) Iain Murray (5) Aaron Courville (5) Eleni Triantafillou (4) Vincent Dumoulin (4) Anirudh Goyal (4) William Fedus (4) Pascal Lamblin (3) Benigno Uria (3)

Keywords

neural network (8) unsupervised learning (8) autoregressive model (6) representation learning (5) generative model (5) density estimation (4) feature learning (4) restricted boltzmann machine (4) image classification (3) few-shot learning (3) topic modeling (3) transfer learning (3) generative adversarial network (3) domain generalization (2) approximate inference (2) greedy layer-wise training (2) neural autoregressive model (2) deep reinforcement learning (2) text generation (2) attention mechanism (2)

Papers

Selective Unlearning via Representation Erasure Using Domain Adversarial Training ICLR 2025
Don't flatten, tokenize! Unlocking the key to SoftMoE's efficacy in deep RL ICLR 2025
Many-Shot In-Context Learning NIPS 2024
Static Prediction of Runtime Errors by Learning to Execute Programs with External Resource Descriptions ICLR 2023
SatBird: a Dataset for Bird Species Distribution Modeling using Remote Sensing and Citizen Science Data NIPS 2023
Repository-Level Prompt Generation for Large Language Models of Code ICML 2023
Fortuitous Forgetting in Connectionist Networks ICLR 2022
Matching Feature Sets for Few-Shot Image Classification CVPR 2022
Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning ICML 2022
Impact of Aliasing on Generalization in Deep Convolutional Networks ICCV 2021
Improving Reproducibility in Machine Learning Research(A Report from the NeurIPS 2019 Reproducibility Program) JMLR 2021
Learning a Universal Template for Few-shot Dataset Generalization ICML 2021
Learning to Combine Per-Example Solutions for Neural Program Synthesis NIPS 2021
DIBS: Diversity Inducing Information Bottleneck in Model Ensembles AAAI 2021
A Universal Representation Transformer Layer for Few-Shot Image Classification ICLR 2021
Algorithmic Improvements for Deep Reinforcement Learning Applied to Interactive Fiction AAAI 2020
Small-GAN: Speeding up GAN Training using Core-Sets ICML 2020
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks NIPS 2020
Learning Graph Structure With A Finite-State Automaton Layer NIPS 2020
Revisiting Fundamentals of Experience Replay ICML 2020
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples ICLR 2020
Language GANs Falling Short ICLR 2020
Curriculum By Smoothing NIPS 2020
Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent Sampling NIPS 2020
InfoBot: Transfer and Exploration via the Information Bottleneck ICLR 2019
Recall Traces: Backtracking Models for Efficient Reinforcement Learning ICLR 2019
Meta-Learning for Semi-Supervised Few-Shot Classification ICLR 2018
A Meta-Learning Perspective on Cold-Start Recommendations for Items NIPS 2017
GuessWhat?! Visual Object Discovery Through Multi-Modal Dialogue CVPR 2017
Modulating early visual processing by language NIPS 2017
Document Neural Autoregressive Distribution Estimation JMLR 2017
Neural Autoregressive Distribution Estimation JMLR 2016
Dynamic Capacity Networks ICML 2016
Domain-Adversarial Training of Neural Networks JMLR 2016
Autoencoding beyond pixels using a learned similarity metric ICML 2016
Using a Recursive Neural Network to Learn an Agent's Decision Model for Plan Recognition IJCAI 2015
Describing Videos by Exploiting Temporal Structure ICCV 2015
MADE: Masked Autoencoder for Distribution Estimation ICML 2015
An Autoencoder Approach to Learning Bilingual Word Representations NIPS 2014
Topic Modeling of Multimodal Data: An Autoregressive Approach CVPR 2014
A Deep and Tractable Density Estimator ICML 2014
Agnostic Bayesian Learning of Ensembles ICML 2014
RNADE: The real-valued neural autoregressive density-estimator NIPS 2013
A Neural Autoregressive Topic Model NIPS 2012
Practical Bayesian Optimization of Machine Learning Algorithms NIPS 2012
On Nonparametric Guidance for Learning Autoencoder Representations AISTATS 2012
Learning Algorithms for the Classification Restricted Boltzmann Machine JMLR 2012
Nonparametric Guidance of Autoencoder Representations using Label Information JMLR 2012
The Neural Autoregressive Distribution Estimator AISTATS 2011
Efficient Learning of Deep Boltzmann Machines AISTATS 2010
Learning to combine foveal glimpses with a third-order Boltzmann machine NIPS 2010
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion JMLR 2010
Exploring Strategies for Training Deep Neural Networks JMLR 2009
Greedy Layer-Wise Training of Deep Networks NIPS 2006