Diet Networks: Thin Parameters for Fat Genomic. - Adriana Romero; Pierre Luc Carrier; Akram Erraqabi; Tristan Sylvain; Alex Auvolat; Etienne Dejoie; Marc-André Legault; Marie-Pierre Dubé; Julie G. Hussin; Yoshua Bengio (CoRR, 2016)

Diet Networks: Thin Parameters for Fat Genomics. - Adriana Romero; Pierre Luc Carrier; Akram Erraqabi; Tristan Sylvain; Alex Auvolat; Etienne Dejoie; Marc-André Legault; Marie-Pierre Dubé; Julie G. Hussin; Yoshua Bengio (ICLR (Poster), 2017)

Deep Learning for Patient-Specific Kidney Graft Survival Analysis. - Margaux Luck; Tristan Sylvain; Héloïse Cardinal; Andrea Lodi 001; Yoshua Bengio (CoRR, 2017)

Learning to rank for censored survival data. - Margaux Luck; Tristan Sylvain; Joseph Paul Cohen; Héloïse Cardinal; Andrea Lodi 001; Yoshua Bengio (CoRR, 2018)

Locality and Compositionality in Zero-Shot Learning. - Tristan Sylvain; Linda Petrini; R. Devon Hjelm (ICLR, 2020)

Joint Learning of Generative Translator and Classifier for Visually Similar Classes. - ByungIn Yoo; Tristan Sylvain; Yoshua Bengio; Junmo Kim 002 (IEEE Access, 2020)

Image-to-image Mapping with Many Domains by Sparse Attribute Transfer. - Matthew Amodio; Rim Assouel; Victor Schmidt; Tristan Sylvain; Smita Krishnaswamy; Yoshua Bengio (CoRR, 2020)

Cross-Modal Information Maximization for Medical Imaging: CMIM. - Tristan Sylvain; Francis Dutil; Tess Berthier; Lisa Di-Jorio; Margaux Luck; R. Devon Hjelm; Yoshua Bengio (CoRR, 2020)

Zero-Shot Learning from scratch (ZFS): leveraging local compositional representations. - Tristan Sylvain; Linda Petrini; R. Devon Hjelm (CoRR, 2020)

On self-supervised multi-modal representation learning: An application to Alzheimer's disease. - Alex Fedorov; Lei Wu 013; Tristan Sylvain; Margaux Luck; Thomas P. DeRamus; Dmitry Bleklov; Sergey M. Plis; Vince D. Calhoun (CoRR, 2020)

Taxonomy of multimodal self-supervised representation learning. - Alex Fedorov; Tristan Sylvain; Margaux Luck; Lei Wu 013; Thomas P. DeRamus; Alex Kirilin; Dmitry Bleklov; Vince D. Calhoun; Sergey M. Plis (CoRR, 2020)

Object-Centric Image Generation from Layouts. - Tristan Sylvain; Pengchuan Zhang; Yoshua Bengio; R. Devon Hjelm; Shikhar Sharma 001 (AAAI, 2021)

CMIM: Cross-Modal Information Maximization For Medical Imaging. - Tristan Sylvain; Francis Dutil; Tess Berthier; Lisa Di-Jorio; Margaux Luck; R. Devon Hjelm; Yoshua Bengio (ICASSP, 2021)

Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease. - Alex Fedorov; Tristan Sylvain; Eloy Geenjaar; Margaux Luck; Lei Wu 013; Thomas P. DeRamus; Alex Kirilin; Dmitry Bleklov; Vince D. Calhoun; Sergey M. Plis (ICHI, 2021)

On Self-Supervised Multimodal Representation Learning: An Application To Alzheimer's Disease. - Alex Fedorov; Lei Wu 013; Tristan Sylvain; Margaux Luck; Thomas P. DeRamus; Dmitry Bleklov; Sergey M. Plis; Vince D. Calhoun (ISBI, 2021)

Exploring the Wasserstein metric for time-to-event analysis. - Tristan Sylvain; Margaux Luck; Joseph Paul Cohen; Héloïse Cardinal; Andrea Lodi 001; Yoshua Bengio (SPACA, 2021)

Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes. - Alex Fedorov; Eloy Geenjaar; Lei Wu 013; Tristan Sylvain; Thomas P. DeRamus; Margaux Luck; Maria B. Misiura; R. Devon Hjelm; Sergey M. Plis; Vince D. Calhoun (CoRR, 2022)

Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting. - Mohammad Amin Shabani; Amir H. Abdi; Lili Meng; Tristan Sylvain (ICLR, 2023)

Robust Reinforcement Learning Objectives for Sequential Recommender Systems. - Melissa Mozifian; Tristan Sylvain; Dave Evans; Lili Meng (CoRR, 2023)

What Constitutes Good Contrastive Learning in Time-Series Forecasting? - Chiyu Zhang; Qi Yan; Lili Meng; Tristan Sylvain (CoRR, 2023)

AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval. - Qi Yan; Raihan Seraj; Jiawei He; Lili Meng; Tristan Sylvain (ICLR, 2024)

OPSurv: Orthogonal Polynomials Quadrature Algorithm for Survival Analysis. - Lilian W. Bialokozowicz; Hoang M. Le; Tristan Sylvain; Peter A. I. Forsyth; Vineel Nagisetty; Greg Mori (CoRR, 2024)

Identifying and Addressing Delusions for Target-Directed Decision-Making. - Mingde Zhao 001; Tristan Sylvain; Doina Precup; Yoshua Bengio (CoRR, 2024)

Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links. - Alex Fedorov; Eloy Geenjaar; Lei Wu 013; Tristan Sylvain; Thomas P. DeRamus; Margaux Luck; Maria B. Misiura; Girish Mittapalle; R. Devon Hjelm; Sergey M. Plis; Vince D. Calhoun (NeuroImage, 2024)

LLM-TS Integrator: Integrating LLM for Enhanced Time Series Modeling. - Can Chen; Gabriel L. Oliveira; Hossein Sharifi-Noghabi; Tristan Sylvain (Trans. Mach. Learn. Res., 2025)

Contextual bandits with entropy-based human feedback. - Raihan Seraj; Lili Meng; Tristan Sylvain (CoRR, 2025)