Ryan Sullivan

According to our database, Ryan Sullivan authored at least 24 papers between 1998 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Syllabus: Portable Curricula for Reinforcement Learning Agents.

Ryan Sullivan, Ryan Pégoud, Ameen Ur Rahmen, Xinchen Yang, Junyun Huang, Aayush Verma, Nistha Mitra, John P. Dickerson

CoRR, 2024

Conditioned Language Policy: A General Framework for Steerable Multi-Objective Finetuning.

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

CoRR, 2024

Massively Multiagent Minigames for Training Generalist Agents.

Kyoung Whan Choe, Ryan Sullivan, Joseph Suárez

CoRR, 2024

How Much Data are Enough? Investigating Dataset Requirements for Patch-Based Brain MRI Segmentation Tasks.

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

CoRR, 2024

Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning.

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

CoRR, 2024

Improving multiple sclerosis lesion segmentation across clinical sites: A federated learning approach with noise-resilient training.

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

Artif. Intell. Medicine, 2024

Conditional Language Policy: A General Framework For Steerable Multi-Objective Finetuning.

Kaiwen Wang, Rahul Kidambi, Ryan Sullivan, Alekh Agarwal, Christoph Dann, Andrea Michi, Marco Gelmi, Yunxuan Li, Raghav Gupta, Kumar Dubey, Alexandre Ramé, Johan Ferret, Geoffrey Cideron, Le Hou, Hongkun Yu, Amr Ahmed, Aranyak Mehta, Léonard Hussenot, Olivier Bachem, Edouard Leurent

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning.

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

CoRR, 2023

Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks.

Ryan Sullivan, Akarsh Kumar, Shengyi Huang, John P. Dickerson, Joseph Suarez

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Gradient Informed Proximal Policy Optimization.

Sanghyun Son, Laura Yu Zheng, Ryan Sullivan, Yi-Ling Qiao, Ming C. Lin

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments.

Ryan Sullivan, Justin K. Terry, Benjamin Black, John P. Dickerson

CoRR, 2022

MS Lesion Segmentation: Revisiting Weighting Mechanisms for Federated Learning.

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

CoRR, 2022

Tracking Large Class Projects in Real-Time Using Fine-Grained Source Control.

Gustavo Rodriguez-Rivera, Jeffrey A. Turkstra, Jordan Buckmaster, Killian LeClainche, Shawn Montgomery, William Reed, Ryan Sullivan, Jarett Lee

Proceedings of the SIGCSE 2022: The 53rd ACM Technical Symposium on Computer Science Education, 2022

Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments.

Ryan Sullivan, Jordan K. Terry, Benjamin Black, John P. Dickerson

Proceedings of the International Conference on Machine Learning, 2022

2021

PettingZoo: Gym for Multi-Agent Reinforcement Learning.

Justin 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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Multi-class semantic segmentation of pediatric chest radiographs.

Gregory Holste, Ryan Sullivan, Michael D. Bindschadler, Nicholas Nagy, Adam M. Alessio

Proceedings of the Medical Imaging 2020: Image Processing, 2020

Deep learning methods for segmentation of lines in pediatric chest radiographs.

Ryan Sullivan, Gregory Holste, Jonathan Burkow, Adam M. Alessio

Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020

2016

Finding Potentially Unsafe Nutritional Supplements from User Reviews with Topic Modeling.

Ryan Sullivan, Abeed Sarker, Karen O'Connor, Amanda Goodin, Mark Karlsrud, Graciela Gonzalez

Proceedings of the Biocomputing 2016: Proceedings of the Pacific Symposium, 2016

2014

Text Classification towards Detecting Misdiagnosis of an Epilepsy Syndrome in a Pediatric Population.

Ryan Sullivan, Robert Yao, Randa Jarar, Jeffrey Buchhalter, Graciela Gonzalez

Proceedings of the AMIA 2014, 2014

2011

The DIEGO Lab Graph Based Gene Normalization System.

Ryan Sullivan, Robert Leaman, Graciela Gonzalez

Proceedings of the 10th International Conference on Machine Learning and Applications and Workshops, 2011

2010

Efficient Extraction of Protein-Protein Interactions from Full-Text Articles.

Jörg Hakenberg, Robert Leaman, Nguyen Ha Vo, Siddhartha Jonnalagadda, Ryan Sullivan, Christopher Miller, Luis Tari, Chitta Baral, Graciela Gonzalez

IEEE ACM Trans. Comput. Biol. Bioinform., 2010

Towards Internet-Age Pharmacovigilance: Extracting Adverse Drug Reactions from User Posts in Health-Related Social Networks.

Robert Leaman, Laura Wojtulewicz, Ryan Sullivan, Annie Skariah, Jian Yang, Graciela Gonzalez

Proceedings of the 2010 Workshop on Biomedical Natural Language Processing, 2010

1998

Active Laser Radar for High Performance Measurements.

John A. Hancock, Dirk Langer, Martial Hebert, Ryan Sullivan, Darin Ingimarson, Eric Hoffmann, Markus Mettenleiter, Christoph Fröhlich

Proceedings of the IEEE International Conference on Robotics and Automation, 1998