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Journal Articles
- 2024
[j2]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:
Improving multiple sclerosis lesion segmentation across clinical sites: A federated learning approach with noise-resilient training. Artif. Intell. Medicine 152: 102872 (2024)- 2010
- [j1]Jörg Hakenberg, Robert Leaman, Nguyen Ha Vo, Siddhartha Jonnalagadda, Ryan Sullivan, Christopher Miller, Luis Tari, Chitta Baral, Graciela Gonzalez:
Efficient Extraction of Protein-Protein Interactions from Full-Text Articles. IEEE ACM Trans. Comput. Biol. Bioinform. 7(3): 481-494 (2010)
Conference and Workshop Papers
- 2023
- [c13]Sanghyun Son, Laura Yu Zheng, Ryan Sullivan, Yi-Ling Qiao, Ming C. Lin:
Gradient Informed Proximal Policy Optimization. NeurIPS 2023 - [c12]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:
Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning. NeurIPS 2023 - [c11]Ryan Sullivan, Akarsh Kumar, Shengyi Huang, John P. Dickerson, Joseph Suarez:
Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks. NeurIPS 2023 - 2022
- [c10]Ryan Sullivan, Jordan K. Terry, Benjamin Black, John P. Dickerson:
Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments. ICML 2022: 20744-20776 - [c9]Gustavo Rodriguez-Rivera, Jeffrey A. Turkstra, Jordan Buckmaster, Killian LeClainche, Shawn Montgomery, William Reed, Ryan Sullivan, Jarett Lee:
Tracking Large Class Projects in Real-Time Using Fine-Grained Source Control. SIGCSE (1) 2022: 565-570 - 2021
- [c8]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:
PettingZoo: Gym for Multi-Agent Reinforcement Learning. NeurIPS 2021: 15032-15043 - 2020
- [c7]Ryan Sullivan, Gregory Holste, Jonathan Burkow, Adam M. Alessio:
Deep learning methods for segmentation of lines in pediatric chest radiographs. Medical Imaging: Computer-Aided Diagnosis 2020 - [c6]Gregory Holste, Ryan Sullivan, Michael D. Bindschadler, Nicholas Nagy, Adam M. Alessio:
Multi-class semantic segmentation of pediatric chest radiographs. Medical Imaging: Image Processing 2020: 113131E - 2016
- [c5]Ryan Sullivan, Abeed Sarker, Karen O'Connor, Amanda Goodin, Mark Karlsrud, Graciela Gonzalez:
Finding Potentially Unsafe Nutritional Supplements from User Reviews with Topic Modeling. PSB 2016: 528-539 - 2014
- [c4]Ryan Sullivan, Robert Yao, Randa Jarar, Jeffrey Buchhalter, Graciela Gonzalez:
Text Classification towards Detecting Misdiagnosis of an Epilepsy Syndrome in a Pediatric Population. AMIA 2014 - 2011
- [c3]Ryan Sullivan, Robert Leaman, Graciela Gonzalez:
The DIEGO Lab Graph Based Gene Normalization System. ICMLA (2) 2011: 78-83 - 2010
- [c2]Robert Leaman, Laura Wojtulewicz, Ryan Sullivan, Annie Skariah, Jian Yang, Graciela Gonzalez:
Towards Internet-Age Pharmacovigilance: Extracting Adverse Drug Reactions from User Posts in Health-Related Social Networks. BioNLP@ACL 2010: 117-125 - 1998
- [c1]John A. Hancock, Dirk Langer, Martial Hebert, Ryan Sullivan, Darin Ingimarson, Eric Hoffmann, Markus Mettenleiter, Christoph Fröhlich:
Active Laser Radar for High Performance Measurements. ICRA 1998: 1465-1470
Informal and Other Publications
- 2024
- [i10]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:
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning. CoRR abs/2402.03046 (2024) - [i9]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:
How Much Data are Enough? Investigating Dataset Requirements for Patch-Based Brain MRI Segmentation Tasks. CoRR abs/2404.03451 (2024) - [i8]Kyoung Whan Choe, Ryan Sullivan, Joseph Suárez:
Massively Multiagent Minigames for Training Generalist Agents. CoRR abs/2406.05071 (2024) - [i7]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:
Conditioned Language Policy: A General Framework for Steerable Multi-Objective Finetuning. CoRR abs/2407.15762 (2024) - 2023
- [i6]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:
Improving Multiple Sclerosis Lesion Segmentation Across Clinical Sites: A Federated Learning Approach with Noise-Resilient Training. CoRR abs/2308.16376 (2023) - [i5]Ryan Sullivan, Akarsh Kumar, Shengyi Huang, John P. Dickerson, Joseph Suarez:
Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks. CoRR abs/2310.17805 (2023) - [i4]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:
Neural MMO 2.0: A Massively Multi-task Addition to Massively Multi-agent Learning. CoRR abs/2311.03736 (2023) - [i3]Sanghyun Son, Laura Yu Zheng, Ryan Sullivan, Yi-Ling Qiao, Ming C. Lin:
Gradient Informed Proximal Policy Optimization. CoRR abs/2312.08710 (2023) - 2022
- [i2]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:
MS Lesion Segmentation: Revisiting Weighting Mechanisms for Federated Learning. CoRR abs/2205.01509 (2022) - [i1]Ryan Sullivan, Justin K. Terry, Benjamin Black, John P. Dickerson:
Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments. CoRR abs/2205.07015 (2022)
Coauthor Index
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