Ryan Sullivan

31 papers A* 7B 1Misc 2Journal 16Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
De-identification of clinical data: A systematic review of free text, image and tabular data approaches.
Int. J. Medical Informatics
Pedro Faustini, Annabelle McIver, Ryan Sullivan, Mark Dras
2025 J jnl
Results of the NeurIPS 2023 Neural MMO Competition on Multi-task Reinforcement Learning.
CoRR
Joseph Suárez, Kyoung Whan Choe, David Bloomin, Jianming Gao, Yunkun Li, Yao Feng, Saidinesh Pola, Kun Zhang, Yonghui Zhu, Nikhil Pinnaparaju, Hao Xiang Li, Nishaanth Kanna, Daniel Scott, Ryan Sullivan, Rose S. Shuman, Lucas de Alcântara, Herbie Bradley, Kirsty You, Bo Wu, Yuhao Jiang, Qimai Li, Jiaxin Chen, Louis Castricato, Xiaolong Zhu, Phillip Isola
2025 A* conf
Robust Multi-Objective Preference Alignment with Online DPO.
AAAI
Raghav Gupta, Ryan Sullivan, Yunxuan Li, Samrat Phatale, Abhinav Rastogi
2025 J jnl
Robust Multi-Objective Preference Alignment with Online DPO.
CoRR
Raghav Gupta, Ryan Sullivan, Yunxuan Li, Samrat Phatale, Abhinav Rastogi
2024 — conf
Conditional Language Policy: A General Framework For Steerable Multi-Objective Finetuning.
EMNLP (Findings)
Kaiwen Wang, Rahul Kidambi, Ryan Sullivan, Alekh Agarwal, Christoph Dann, Andrea Michi, Marco Gelmi, Yunxuan Li, Raghav Gupta, Avinava Dubey, Alexandre Ramé, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Léonard Hussenot, Olivier Bachem, Edouard Leurent
2024 J jnl
Conditioned Language Policy: A General Framework for Steerable Multi-Objective Finetuning.
CoRR
Kaiwen Wang, Rahul Kidambi, Ryan Sullivan, Alekh Agarwal, Christoph Dann, Andrea Michi, Marco Gelmi, Yunxuan Li, Raghav Gupta, Avinava Dubey, Alexandre Ramé, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Léonard Hussenot, Olivier Bachem, Edouard Leurent
2024 J jnl
How Much Data are Enough? Investigating Dataset Requirements for Patch-Based Brain MRI Segmentation Tasks.
CoRR
Dongang Wang, Peilin Liu, Hengrui Wang, Heidi Beadnall, Kain Kyle, Linda Ly, Mariano Cabezas, Geng Zhan, Ryan Sullivan, Tom Weidong Cai, Wanli Ouyang, Fernando Calamante, Michael Barnett, Chenyu Wang
2024 J jnl
Improving multiple sclerosis lesion segmentation across clinical sites: A federated learning approach with noise-resilient training.
Artif. Intell. Medicine
Lei Bai, Dongang Wang, Hengrui Wang, Michael Barnett, Mariano Cabezas, Weidong Cai, Fernando Calamante, Kain Kyle, Dongnan Liu, Linda Ly, Aria Nguyen, Chun-Chien Shieh, Ryan Sullivan, Geng Zhan, Wanli Ouyang, Chenyu Wang
2024 J jnl
Massively Multiagent Minigames for Training Generalist Agents.
CoRR
Kyoung Whan Choe, Ryan Sullivan, Joseph Suárez
2024 J jnl
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning.
CoRR
Shengyi Huang, Quentin Gallouédec, Florian Felten, Antonin Raffin, Rousslan Fernand Julien Dossa, Yanxiao Zhao, Ryan Sullivan, Viktor Makoviychuk, Denys Makoviichuk, Mohamad H. Danesh, Cyril Roumégous, Jiayi Weng, Chufan Chen, Md Masudur Rahman, João G. M. Araújo, Guorui Quan, Daniel Tan, Timo Klein, Rujikorn Charakorn, Mark Towers, Yann Berthelot, Kinal Mehta, Dipam Chakraborty, Arjun KG, Valentin Charraut, Chang Ye, Zichen Liu, Lucas N. Alegre, Alexander Nikulin, Xiao Hu, Tianlin Liu, Jongwook Choi, Brent Yi
2024 J jnl
Syllabus: Portable Curricula for Reinforcement Learning Agents.
CoRR
Ryan Sullivan, Ryan Pégoud, Ameen Ur Rahmen, Xinchen Yang, Junyun Huang, Aayush Verma, Nistha Mitra, John P. Dickerson
2023 A* conf
Gradient Informed Proximal Policy Optimization.
NeurIPS
Sanghyun Son, Laura Yu Zheng, Ryan Sullivan, Yi-Ling Qiao, Ming C. Lin
2023 J jnl
Gradient Informed Proximal Policy Optimization.
CoRR
Sanghyun Son, Laura Yu Zheng, Ryan Sullivan, Yi-Ling Qiao, Ming C. Lin
2023 J jnl
Improving Multiple Sclerosis Lesion Segmentation Across Clinical Sites: A Federated Learning Approach with Noise-Resilient Training.
CoRR
Lei Bai, Dongang Wang, Michael Barnett, Mariano Cabezas, Weidong Cai, Fernando Calamante, Kain Kyle, Dongnan Liu, Linda Ly, Aria Nguyen, Chun-Chien Shieh, Ryan Sullivan, Hengrui Wang, Geng Zhan, Wanli Ouyang, Chenyu Wang
2023 A* conf
Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning.
NeurIPS
Joseph Suarez, David Bloomin, Kyoung Whan Choe, Hao Xiang Li, Ryan Sullivan, Nishaanth Kanna, Daniel Scott, Rose S. Shuman, Herbie Bradley, Louis Castricato, Phillip Isola, ChengHui Yu, Yuhao Jiang, Qimai Li, Jiaxin Chen, Xiaolong Zhu
2023 J jnl
Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning.
CoRR
Joseph Suárez, Phillip Isola, Kyoung Whan Choe, David Bloomin, Hao Xiang Li, Nikhil Pinnaparaju, Nishaanth Kanna, Daniel Scott, Ryan Sullivan, Rose S. Shuman, Lucas de Alcântara, Herbie Bradley, Louis Castricato, Kirsty You, Yuhao Jiang, Qimai Li, Jiaxin Chen, Xiaolong Zhu
2023 A* conf
Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks.
NeurIPS
Ryan Sullivan, Akarsh Kumar, Shengyi Huang, John P. Dickerson, Joseph Suarez
2023 J jnl
Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks.
CoRR
Ryan Sullivan, Akarsh Kumar, Shengyi Huang, John P. Dickerson, Joseph Suarez
2022 A* conf
Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments.
ICML
Ryan Sullivan, J. K. Terry, Benjamin Black, John P. Dickerson
2022 J jnl
Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments.
CoRR
Ryan Sullivan, J. K. Terry, Benjamin Black, John P. Dickerson
2022 J jnl
MS Lesion Segmentation: Revisiting Weighting Mechanisms for Federated Learning.
CoRR
Dongnan Liu, Mariano Cabezas, Dongang Wang, Zihao Tang, Lei Bai, Geng Zhan, Yuling Luo, Kain Kyle, Linda Ly, James Yu, Chun-Chien Shieh, Aria Nguyen, Ettikan Kandasamy Karuppiah, Ryan Sullivan, Fernando Calamante, Michael Barnett, Wanli Ouyang, Weidong Cai, Chenyu Wang
2022 — conf
Tracking Large Class Projects in Real-Time Using Fine-Grained Source Control.
SIGCSE (1)
Gustavo Rodriguez-Rivera, Jeffrey A. Turkstra, Jordan Buckmaster, Killian LeClainche, Shawn Montgomery, William Reed, Ryan Sullivan, Jarett Lee
2021 A* conf
PettingZoo: Gym for Multi-Agent Reinforcement Learning.
NeurIPS
J. K. Terry, Benjamin Black, Nathaniel Grammel, Mario Jayakumar, Ananth Hari, Ryan Sullivan, Luis S. Santos, Clemens Dieffendahl, Caroline Horsch, Rodrigo Perez-Vicente, Niall L. Williams, Yashas Lokesh, Praveen Ravi
2020 — conf
Deep learning methods for segmentation of lines in pediatric chest radiographs.
Computer-Aided Diagnosis
Ryan Sullivan, Gregory Holste, Jonathan Burkow, Adam M. Alessio
2020 B conf
Multi-class semantic segmentation of pediatric chest radiographs.
Image Processing
Gregory Holste, Ryan Sullivan, Michael D. Bindschadler, Nicholas Nagy, Adam M. Alessio
2016 Misc conf
Finding Potentially Unsafe Nutritional Supplements from User Reviews with Topic Modeling.
PSB
Ryan Sullivan, Abeed Sarker, Karen O'Connor, Amanda Goodin, Mark Karlsrud, Graciela Gonzalez
2014 Misc conf
Text Classification towards Detecting Misdiagnosis of an Epilepsy Syndrome in a Pediatric Population.
AMIA
Ryan Sullivan, Robert Yao, Randa Jarar, Jeffrey Buchhalter, Graciela Gonzalez
2011 — conf
The DIEGO Lab Graph Based Gene Normalization System.
ICMLA (2)
Ryan Sullivan, Robert Leaman, Graciela Gonzalez
2010 J jnl
Efficient Extraction of Protein-Protein Interactions from Full-Text Articles.
IEEE ACM Trans. Comput. Biol. Bioinform.
Jörg Hakenberg, Robert Leaman, Nguyen Ha Vo, Siddhartha Jonnalagadda, Ryan Sullivan, Christopher Miller, Luis Tari, Chitta Baral, Graciela Gonzalez
2010 — conf
Towards Internet-Age Pharmacovigilance: Extracting Adverse Drug Reactions from User Posts in Health-Related Social Networks.
BioNLP@ACL
Robert Leaman, Laura Wojtulewicz, Ryan Sullivan, Annie Skariah, Jian Yang, Graciela Gonzalez
1998 A* conf
Active Laser Radar for High Performance Measurements.
ICRA
John A. Hancock, Dirk Langer, Martial Hebert, Ryan Sullivan, Darin Ingimarson, Eric Hoffmann, Markus Mettenleiter, Christoph Fröhlich