Tristan Sylvain

Orcid: 0000-0001-5390-4036

According to our database¹, Tristan Sylvain authored at least 25 papers between 2016 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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PhD thesis

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Links

On csauthors.net:

Bibliography

2024

Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links.

[BibT_eX]

[DOI]

NeuroImage, January, 2024

LLM-TS Integrator: Integrating LLM for Enhanced Time Series Modeling.

[BibT_eX]

[DOI]

Can Chen

Gabriel Oliveira

Hossein Sharifi Noghabi

Tristan Sylvain

CoRR, 2024

Identifying and Addressing Delusions for Target-Directed Decision-Making.

[BibT_eX]

[DOI]

CoRR, 2024

OPSurv: Orthogonal Polynomials Quadrature Algorithm for Survival Analysis.

[BibT_eX]

[DOI]

Lilian W. Bialokozowicz

CoRR, 2024

AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

What Constitutes Good Contrastive Learning in Time-Series Forecasting?

[BibT_eX]

[DOI]

CoRR, 2023

Robust Reinforcement Learning Objectives for Sequential Recommender Systems.

[BibT_eX]

[DOI]

CoRR, 2023

Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting.

[BibT_eX]

[DOI]

Mohammad Amin Shabani

Amir H. Abdi

Lili Meng

Tristan Sylvain

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Exploring the Wasserstein metric for time-to-event analysis.

[BibT_eX]

[DOI]

Proceedings of AAAI Symposium on Survival Prediction, 2021

On Self-Supervised Multimodal Representation Learning: An Application To Alzheimer's Disease.

[BibT_eX]

[DOI]

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease.

[BibT_eX]

[DOI]

Proceedings of the 9th IEEE International Conference on Healthcare Informatics, 2021

CMIM: Cross-Modal Information Maximization For Medical Imaging.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Acoustics, 2021

Object-Centric Image Generation from Layouts.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Taxonomy of multimodal self-supervised representation learning.

[BibT_eX]

[DOI]

CoRR, 2020

On self-supervised multi-modal representation learning: An application to Alzheimer's disease.

[BibT_eX]

[DOI]

CoRR, 2020

Zero-Shot Learning from scratch (ZFS): leveraging local compositional representations.

[BibT_eX]

[DOI]

Tristan Sylvain

Linda Petrini

R. Devon Hjelm

CoRR, 2020

Cross-Modal Information Maximization for Medical Imaging: CMIM.

[BibT_eX]

[DOI]

CoRR, 2020

Image-to-image Mapping with Many Domains by Sparse Attribute Transfer.

[BibT_eX]

[DOI]

CoRR, 2020

Joint Learning of Generative Translator and Classifier for Visually Similar Classes.

[BibT_eX]

[DOI]

IEEE Access, 2020

Locality and Compositionality in Zero-Shot Learning.

[BibT_eX]

[DOI]

Tristan Sylvain

Linda Petrini

R. Devon Hjelm

Proceedings of the 8th International Conference on Learning Representations, 2020

2018

Learning to rank for censored survival data.

[BibT_eX]

[DOI]

CoRR, 2018

2017

Deep Learning for Patient-Specific Kidney Graft Survival Analysis.

[BibT_eX]

[DOI]

CoRR, 2017

Diet Networks: Thin Parameters for Fat Genomics.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Diet Networks: Thin Parameters for Fat Genomic.

[BibT_eX]

[DOI]

CoRR, 2016

Tristan Sylvain

Timeline

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