← Authors

Youssef Mroueh

33 papers · 2012–2026 · 8 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (13) 🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (8) πŸ—ΊοΈ Taxonomy Completionist (10) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸ”¬ Deep Specialist (10) πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (134) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ’Ž Century Club (32) πŸ”₯ Unstoppable (9) ⚑ Prolific Year (5)

Conferences

NIPS (10) AISTATS (8) ICLR (6) ICML (3) AAAI (2) CVPR (2) ACL (1) ICCV (1)

Top co-authors

Tom Sercu (7) Jarret Ross (5) Mattia Rigotti (5) Payel Das (5) Igor Melnyk (4) Kristjan Greenewald (4) Pierre Dognin (4) Brian Belgodere (3) Jiri Navratil (3) Inkit Padhi (3)

Keywords

optimal transport (8) generative adversarial network (7) kernel methods (6) integral probability metric (3) maximum mean discrepancy (3) style transfer (3) implicit generative model (3) transfer learning (2) generative model (2) random feature map (2) feature learning (2) reproducing kernel hilbert space (2) kernel approximation (2) adversarial learning (2) image captioning (2) distribution matching (2) feature matching (2) stochastic dominance (2) moment matching (2) self-critical sequence training (2)

Papers

GP-MoLFormer-Sim: Test Time Molecular Optimization Through Contextual Similarity Guidance AAAI 2026
Large Language Models can Become Strong Self-Detoxifiers ICLR 2025
Distributional Preference Alignment of LLMs via Optimal Transport NIPS 2024
Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking NIPS 2024
Risk Aware Benchmarking of Large Language Models ICML 2024
Learning with Stochastic Orders ICLR 2023
Tighter Sparse Approximation Bounds for ReLU Neural Networks ICLR 2022
Cycle Consistent Probability Divergences Across Different Spaces AISTATS 2022
Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics NIPS 2021
Measuring Generalization with Optimal Transport NIPS 2021
Improved Mutual Information Estimation AAAI 2021
On the Convergence of Gradient Descent in GANs: MMD GAN As a Gradient Flow AISTATS 2021
Fair Mixup: Fairness via Interpolation ICLR 2021
Wasserstein Style Transfer AISTATS 2020
A Decentralized Parallel Algorithm for Training Generative Adversarial Nets NIPS 2020
Unbalanced Sobolev Descent NIPS 2020
Learning Implicit Text Generation via Feature Matching ACL 2020
Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic Spaces AISTATS 2020
Towards Better Understanding of Adaptive Gradient Algorithms in Generative Adversarial Nets ICLR 2020
Implicit Kernel Learning AISTATS 2019
Sobolev Descent AISTATS 2019
Adversarial Semantic Alignment for Improved Image Captions CVPR 2019
Learning Implicit Generative Models by Matching Perceptual Features ICCV 2019
Sobolev Independence Criterion NIPS 2019
Sobolev GAN ICLR 2018
Local Group Invariant Representations via Orbit Embeddings AISTATS 2017
Self-Critical Sequence Training for Image Captioning CVPR 2017
Co-Occurring Directions Sketching for Approximate Matrix Multiply AISTATS 2017
McGan: Mean and Covariance Feature Matching GAN ICML 2017
Fisher GAN NIPS 2017
Learning with Group Invariant Features: A Kernel Perspective. NIPS 2015
Convex Learning of Multiple Tasks and their Structure ICML 2015
Multiclass Learning with Simplex Coding NIPS 2012