Vincent Jeanselme

21 papers Journal 16Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	One Loss to Rule Them All: Marked Time-to-Event for Structured EHR Foundation Models. CoRR Zilin Jing, Vincent Jeanselme, Yuta Kobayashi, Simon A. Lee, Chao Pang, Aparajita Kashyap, Yanwei Li, Xinzhuo Jiang, Shalmali Joshi
2025	—	`conf`	ADHAM: Additive Deep Hazard Analysis Mixtures for Interpretable Survival Regression. MLHC Mert Ketenci, Vincent Jeanselme, Harry Reyes Nieva, Shalmali Joshi, Noémie Elhadad
2025	J	`jnl`	ADHAM: Additive Deep Hazard Analysis Mixtures for Interpretable Survival Regression. CoRR Mert Ketenci, Vincent Jeanselme, Harry Reyes Nieva, Shalmali Joshi, Noémie Elhadad
2025	J	`jnl`	Competing Risks: Impact on Risk Estimation and Algorithmic Fairness. CoRR Vincent Jeanselme, Brian D. M. Tom, Jessica K. Barrett
2025	J	`jnl`	FoMoH: A clinically meaningful foundation model evaluation for structured electronic health records. CoRR Chao Pang, Vincent Jeanselme, Young Sang Choi, Xinzhuo Jiang, Zilin Jing, Aparajita Kashyap, Yuta Kobayashi, Yanwei Li, Florent Pollet, Karthik Natarajan, Shalmali Joshi
2025	J	`jnl`	ICYM2I: The illusion of multimodal informativeness under missingness. CoRR Young Sang Choi, Vincent Jeanselme, Pierre A. Elias, Shalmali Joshi
2025	J	`jnl`	Leveraging Expert Consistency to Improve Algorithmic Decision Support. Manag. Sci. Maria De-Arteaga, Vincent Jeanselme, Artur Dubrawski, Alexandra Chouldechova
2025	J	`jnl`	Mind the data gap: Missingness Still Shapes Large Language Model Prognoses. CoRR Yuta Kobayashi, Vincent Jeanselme, Shalmali Joshi
2025	J	`jnl`	Prediction of Survival Outcomes under Clinical Presence Shift: A Joint Neural Network Architecture. CoRR Vincent Jeanselme, Glen P. Martin, Matthew Sperrin, Niels Peek, Brian D. M. Tom, Jessica K. Barrett
2025	J	`jnl`	Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025. CoRR Emily Alsentzer, Marie-Laure Charpignon, Bill Chen, Niharika D'Souza, Jason A. Fries, Yixing Jiang, Aparajita Kashyap, Chanwoo Kim, Simon A. Lee, Aishwarya Mandyam, Ashery Christopher Mbilinyi, Nikita Mehandru, Nitish Nagesh, Brighton Nuwagira, Emma Pierson, Arvind Pillai, Akane Sano, Tanveer F. Syeda-Mahmood, Shashank Yadav, Elias Adhanom, Muhammad Umar Afza, Amelia Archer, Suhana Bedi, Vasiliki Bikia, Trenton Chang, George H. Chen, Winston Chen, Erica Chiang, Edward Choi, Octavia Ciora, Paz Dozie-Nnamah, Shaza Elsharief, Matthew Engelhard, Ali Eshragh, Jean Feng, Josh Fessel, Scott L. Fleming, Kei Sen Fong, Thomas Frost, Soham Gadgil, Judy Gichoya, Leeor Hershkovich, Sujeong Im, Bhavya Jain, Vincent Jeanselme, Furong Jia, Qixuan Jin, Yuxuan Jin, Daniel Kapash, Geetika Kapoor, Behdokht Kiafar, Matthias Kleiner, Stefan Kraft, Annika Kumar, Daeun Kyung, Zhongyuan Liang, Joanna Lin, Qianchu Liu, Chang Liu, Hongzhou Luan, Chris Lunt, Leopoldo Julian Lechuga López, Matthew B. A. McDermott, Shahriar Noroozizadeh, Connor O'Brien, YongKyung Oh, Mixail Ota, Stephen Pfohl, Meagan Pi, Tanmoy Sarkar Pias, Emma Rocheteau, Avishaan Sethi, Toru Shirakawa, Anita Silver, Neha Simha, Kamile Stankeviciute, Max Sunog, Peter Szolovits, Shengpu Tang, Jialu Tang, Aaron Tierney, John Valdovinos, Byron Wallace, Will Ke Wang, Peter Washington, Jeremy C. Weiss, Daniel Wolfe, Emily Wong, Hye Sun Yun, Xiaoman Zhang, Xiao Yu Cindy Zhang, Hayoung Jeong, Kaveri A. Thakoor
2024	J	`jnl`	Constrained clustering and multiple kernel learning without pairwise constraint relaxation. Adv. Data Anal. Classif. Benedikt Boecking, Vincent Jeanselme, Artur Dubrawski
2024	J	`jnl`	Identifying treatment response subgroups in observational time-to-event data. CoRR Vincent Jeanselme, Chang Ho Yoon, Fabian Falck, Brian D. M. Tom, Jessica K. Barrett
2024	J	`jnl`	Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai Orson Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gürsoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo
2023	—	`conf`	Neural Fine-Gray: Monotonic neural networks for competing risks. CHIL Vincent Jeanselme, Chang Ho Yoon, Brian D. M. Tom, Jessica K. Barrett
2023	J	`jnl`	Neural Fine-Gray: Monotonic neural networks for competing risks. CoRR Vincent Jeanselme, Chang Ho Yoon, Brian D. M. Tom, Jessica K. Barrett
2022	J	`jnl`	Constrained Clustering and Multiple Kernel Learning without Pairwise Constraint Relaxation. CoRR Benedikt Boecking, Vincent Jeanselme, Artur Dubrawski
2022	J	`jnl`	DeepJoint: Robust Survival Modelling Under Clinical Presence Shift. CoRR Vincent Jeanselme, Glen P. Martin, Niels Peek, Matthew Sperrin, Brian D. M. Tom, Jessica K. Barrett
2022	—	`conf`	Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness. ML4H@NeurIPS Vincent Jeanselme, Maria De-Arteaga, Zhe Zhang, Jessica K. Barrett, Brian D. M. Tom
2022	J	`jnl`	Imputation Strategies Under Clinical Presence: Impact on Algorithmic Fairness. CoRR Vincent Jeanselme, Maria De-Arteaga, Zhe Zhang, Jessica K. Barrett, Brian D. M. Tom
2022	—	`conf`	Neural Survival Clustering: Non-parametric mixture of neural networks for survival clustering. CHIL Vincent Jeanselme, Brian D. M. Tom, Jessica K. Barrett
2021	—	`conf`	Deep Parametric Time-to-Event Regression with Time-Varying Covariates. SPACA Chirag Nagpal, Vincent Jeanselme, Artur Dubrawski