Tristan Sylvain

33 papers A* 5Misc 1Journal 23Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Contextual bandits with entropy-based human feedback. CoRR Raihan Seraj, Lili Meng, Tristan Sylvain
2025	J	`jnl`	LLM-TS Integrator: Integrating LLM for Enhanced Time Series Modeling. Trans. Mach. Learn. Res. Can Chen, Gabriel L. Oliveira, Hossein Sharifi-Noghabi, Tristan Sylvain
2025	A*	`conf`	Rejecting Hallucinated State Targets during Planning. ICML Harry Zhao, Tristan Sylvain, Romain Laroche, Doina Precup, Yoshua Bengio
2024	A*	`conf`	AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval. ICLR Qi Yan, Raihan Seraj, Jiawei He, Lili Meng, Tristan Sylvain
2024	J	`jnl`	Identifying and Addressing Delusions for Target-Directed Decision-Making. CoRR Mingde Zhao, Tristan Sylvain, Doina Precup, Yoshua Bengio
2024	J	`jnl`	LLM-TS Integrator: Integrating LLM for Enhanced Time Series Modeling. CoRR Can Chen, Gabriel L. Oliveira, Hossein Sharifi Noghabi, Tristan Sylvain
2024	J	`jnl`	OPSurv: Orthogonal Polynomials Quadrature Algorithm for Survival Analysis. CoRR Lilian W. Bialokozowicz, Hoang M. Le, Tristan Sylvain, Peter A. I. Forsyth, Vineel Nagisetty, Greg Mori
2024	J	`jnl`	Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links. NeuroImage 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
2023	J	`jnl`	AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval. CoRR Qi Yan, Raihan Seraj, Jiawei He, Lili Meng, Tristan Sylvain
2023	J	`jnl`	Robust Reinforcement Learning Objectives for Sequential Recommender Systems. CoRR Melissa Mozifian, Tristan Sylvain, Dave Evans, Lili Meng
2023	A*	`conf`	Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting. ICLR Mohammad Amin Shabani, Amir H. Abdi, Lili Meng, Tristan Sylvain
2023	J	`jnl`	What Constitutes Good Contrastive Learning in Time-Series Forecasting? CoRR Chiyu Zhang, Qi Yan, Lili Meng, Tristan Sylvain
2022	J	`jnl`	Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting. CoRR Amin Shabani, Amir H. Abdi, Lili Meng, Tristan Sylvain
2022	J	`jnl`	Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes. CoRR 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
2021	Misc	`conf`	CMIM: Cross-Modal Information Maximization For Medical Imaging. ICASSP Tristan Sylvain, Francis Dutil, Tess Berthier, Lisa Di-Jorio, Margaux Luck, R. Devon Hjelm, Yoshua Bengio
2021	—	`conf`	Exploring the Wasserstein metric for time-to-event analysis. SPACA Tristan Sylvain, Margaux Luck, Joseph Paul Cohen, Héloïse Cardinal, Andrea Lodi, Yoshua Bengio
2021	A*	`conf`	Object-Centric Image Generation from Layouts. AAAI Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio, R. Devon Hjelm, Shikhar Sharma
2021	—	`conf`	On Self-Supervised Multimodal Representation Learning: An Application To Alzheimer's Disease. ISBI Alex Fedorov, Lei Wu, Tristan Sylvain, Margaux Luck, Thomas P. DeRamus, Dmitry Bleklov, Sergey M. Plis, Vince D. Calhoun
2021	—	`conf`	Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease. ICHI Alex Fedorov, Tristan Sylvain, Eloy Geenjaar, Margaux Luck, Lei Wu, Thomas P. DeRamus, Alex Kirilin, Dmitry Bleklov, Vince D. Calhoun, Sergey M. Plis
2020	J	`jnl`	Cross-Modal Information Maximization for Medical Imaging: CMIM. CoRR Tristan Sylvain, Francis Dutil, Tess Berthier, Lisa Di-Jorio, Margaux Luck, R. Devon Hjelm, Yoshua Bengio
2020	J	`jnl`	Image-to-image Mapping with Many Domains by Sparse Attribute Transfer. CoRR Matthew Amodio, Rim Assouel, Victor Schmidt, Tristan Sylvain, Smita Krishnaswamy, Yoshua Bengio
2020	J	`jnl`	Joint Learning of Generative Translator and Classifier for Visually Similar Classes. IEEE Access ByungIn Yoo, Tristan Sylvain, Yoshua Bengio, Junmo Kim
2020	A*	`conf`	Locality and Compositionality in Zero-Shot Learning. ICLR Tristan Sylvain, Linda Petrini, R. Devon Hjelm
2020	J	`jnl`	Object-Centric Image Generation from Layouts. CoRR Tristan Sylvain, Pengchuan Zhang, Yoshua Bengio, R. Devon Hjelm, Shikhar Sharma
2020	J	`jnl`	On self-supervised multi-modal representation learning: An application to Alzheimer's disease. CoRR Alex Fedorov, Lei Wu, Tristan Sylvain, Margaux Luck, Thomas P. DeRamus, Dmitry Bleklov, Sergey M. Plis, Vince D. Calhoun
2020	J	`jnl`	Taxonomy of multimodal self-supervised representation learning. CoRR Alex Fedorov, Tristan Sylvain, Margaux Luck, Lei Wu, Thomas P. DeRamus, Alex Kirilin, Dmitry Bleklov, Vince D. Calhoun, Sergey M. Plis
2020	J	`jnl`	Zero-Shot Learning from scratch (ZFS): leveraging local compositional representations. CoRR Tristan Sylvain, Linda Petrini, R. Devon Hjelm
2019	J	`jnl`	Joint Learning of Generative Translator and Classifier for Visually Similar Classes. CoRR ByungIn Yoo, Tristan Sylvain, Yoshua Bengio, Junmo Kim
2019	J	`jnl`	Locality and compositionality in zero-shot learning. CoRR Tristan Sylvain, Linda Petrini, R. Devon Hjelm
2018	J	`jnl`	Learning to rank for censored survival data. CoRR Margaux Luck, Tristan Sylvain, Joseph Paul Cohen, Héloïse Cardinal, Andrea Lodi, Yoshua Bengio
2017	J	`jnl`	Deep Learning for Patient-Specific Kidney Graft Survival Analysis. CoRR Margaux Luck, Tristan Sylvain, Héloïse Cardinal, Andrea Lodi, Yoshua Bengio
2017	—	`conf`	Diet Networks: Thin Parameters for Fat Genomics. ICLR (Poster) Adriana Romero, Pierre Luc Carrier, Akram Erraqabi, Tristan Sylvain, Alex Auvolat, Etienne Dejoie, Marc-André Legault, Marie-Pierre Dubé, Julie G. Hussin, Yoshua Bengio
2016	J	`jnl`	Diet Networks: Thin Parameters for Fat Genomic. CoRR Adriana Romero, Pierre Luc Carrier, Akram Erraqabi, Tristan Sylvain, Alex Auvolat, Etienne Dejoie, Marc-André Legault, Marie-Pierre Dubé, Julie G. Hussin, Yoshua Bengio