Tristan Sylvain

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 28

Top Topics

Learning Objectives

Retrieval Quality

Survival Analysis

Caenorhabditis Elegans

Top Venues

Publications

Lilian W. Bialokozowicz, Hoang M. Le, Tristan Sylvain, Peter A. I. Forsyth, Vineel Nagisetty, Greg Mori
OPSurv: Orthogonal Polynomials Quadrature Algorithm for Survival Analysis. CoRR (2024)
Qi Yan, Raihan Seraj, Jiawei He, Lili Meng, Tristan Sylvain
AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval. ICLR (2024)
Alex Fedorov, Eloy Geenjaar, Lei Wu, Tristan Sylvain, Thomas P. DeRamus, Margaux Luck, Maria B. Misiura, Girish Mittapalle, R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun
Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links. NeuroImage 285 (2024)
Melissa Mozifian, Tristan Sylvain, Dave Evans, Lili Meng
Robust Reinforcement Learning Objectives for Sequential Recommender Systems. CoRR (2023)
Qi Yan, Raihan Seraj, Jiawei He, Lili Meng, Tristan Sylvain
AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval. CoRR (2023)
Mohammad Amin Shabani, Amir H. Abdi, Lili Meng, Tristan Sylvain
Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting. ICLR (2023)
Chiyu Zhang, Qi Yan, Lili Meng, Tristan Sylvain
What Constitutes Good Contrastive Learning in Time-Series Forecasting? CoRR (2023)
Alex Fedorov, Eloy Geenjaar, Lei Wu, Tristan Sylvain, Thomas P. DeRamus, Margaux Luck, Maria B. Misiura, R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun
Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes. CoRR (2022)
Amin Shabani, Amir Abdi, Lili Meng, Tristan Sylvain
Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting. CoRR (2022)
Alex Fedorov, Tristan Sylvain, Eloy Geenjaar, Margaux Luck, Lei Wu, Thomas P. DeRamus, Alex Kirilin, Dmitry Bleklov, Vince D. Calhoun, Sergey M. Plis
Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease. ICHI (2021)
Tristan Sylvain, Francis Dutil, Tess Berthier, Lisa Di-Jorio, Margaux Luck, R. Devon Hjelm, Yoshua Bengio
CMIM: Cross-Modal Information Maximization For Medical Imaging. ICASSP (2021)
Alex Fedorov, Lei Wu, Tristan Sylvain, Margaux Luck, Thomas P. DeRamus, Dmitry Bleklov, Sergey M. Plis, Vince D. Calhoun
On Self-Supervised Multimodal Representation Learning: An Application To Alzheimer's Disease. ISBI (2021)
Tristan Sylvain, Margaux Luck, Joseph Paul Cohen, Héloïse Cardinal, Andrea Lodi, Yoshua Bengio
Exploring the Wasserstein metric for time-to-event analysis. SPACA (2021)
Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio, R. Devon Hjelm, Shikhar Sharma
Object-Centric Image Generation from Layouts. AAAI (2021)
Tristan Sylvain, Linda Petrini, R. Devon Hjelm
Zero-Shot Learning from scratch (ZFS): leveraging local compositional representations. CoRR (2020)
Alex Fedorov, Tristan Sylvain, Margaux Luck, Lei Wu, Thomas P. DeRamus, Alex Kirilin, Dmitry Bleklov, Vince D. Calhoun, Sergey M. Plis
Taxonomy of multimodal self-supervised representation learning. CoRR (2020)
Matthew Amodio, Rim Assouel, Victor Schmidt, Tristan Sylvain, Smita Krishnaswamy, Yoshua Bengio
Image-to-image Mapping with Many Domains by Sparse Attribute Transfer. CoRR (2020)
Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio, R. Devon Hjelm, Shikhar Sharma
Object-Centric Image Generation from Layouts. CoRR (2020)
Tristan Sylvain, Francis Dutil, Tess Berthier, Lisa Di-Jorio, Margaux Luck, R. Devon Hjelm, Yoshua Bengio
Cross-Modal Information Maximization for Medical Imaging: CMIM. CoRR (2020)
Alex Fedorov, Lei Wu, Tristan Sylvain, Margaux Luck, Thomas P. DeRamus, Dmitry Bleklov, Sergey M. Plis, Vince D. Calhoun
On self-supervised multi-modal representation learning: An application to Alzheimer's disease. CoRR (2020)
Tristan Sylvain, Linda Petrini, R. Devon Hjelm
Locality and Compositionality in Zero-Shot Learning. ICLR (2020)
ByungIn Yoo, Tristan Sylvain, Yoshua Bengio, Junmo Kim
Joint Learning of Generative Translator and Classifier for Visually Similar Classes. IEEE Access 8 (2020)
ByungIn Yoo, Tristan Sylvain, Yoshua Bengio, Junmo Kim
Joint Learning of Generative Translator and Classifier for Visually Similar Classes. CoRR (2019)
Tristan Sylvain, Linda Petrini, R. Devon Hjelm
Locality and compositionality in zero-shot learning. CoRR (2019)
Margaux Luck, Tristan Sylvain, Joseph Paul Cohen, Héloïse Cardinal, Andrea Lodi, Yoshua Bengio
Learning to rank for censored survival data. CoRR (2018)
Margaux Luck, Tristan Sylvain, Héloïse Cardinal, Andrea Lodi, Yoshua Bengio
Deep Learning for Patient-Specific Kidney Graft Survival Analysis. CoRR (2017)
Adriana Romero, Pierre Luc Carrier, Akram Erraqabi, Tristan Sylvain, Alex Auvolat, Etienne Dejoie, Marc-André Legault, Marie-Pierre Dubé, Julie G. Hussin, Yoshua Bengio
Diet Networks: Thin Parameters for Fat Genomics. ICLR (Poster) (2017)
Adriana Romero, Pierre Luc Carrier, Akram Erraqabi, Tristan Sylvain, Alex Auvolat, Etienne Dejoie, Marc-André Legault, Marie-Pierre Dubé, Julie G. Hussin, Yoshua Bengio
Diet Networks: Thin Parameters for Fat Genomic. CoRR (2016)