Sharada P. Mohanty

32 papers A 1Journal 21Unranked 10
YearRankTypeTitle / Venue / Authors
2025 J jnl
Decentralized Social Media and Artificial Intelligence in Digital Public Health Monitoring.
CoRR
Marcel Salathé, Sharada P. Mohanty
2024 J jnl
The Sound Demixing Challenge 2023 - Music Demixing Track.
Trans. Int. Soc. Music. Inf. Retr.
Giorgio Fabbro, Stefan Uhlich, Chieh-Hsin Lai, Woosung Choi, Marco A. Martínez Ramírez, Wei-Hsiang Liao, Igor Gadelha, Geraldo Ramos, Eddie Hsu, Hugo Rodrigues, Fabian-Robert Stöter, Alexandre Défossez, Yi Luo, Jianwei Yu, Dipam Chakraborty, Sharada P. Mohanty, Roman A. Solovyev, Alexander L. Stempkovskiy, Tatiana Habruseva, Nabarun Goswami, Tatsuya Harada, Minseok Kim, Jun Hyung Lee, Yuanliang Dong, Xinran Zhang, Jiafeng Liu, Yuki Mitsufuji
2023 A conf
Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMO.
AAMAS
Yangkun Chen, Joseph Suarez, Junjie Zhang, ChengHui Yu, Bo Wu, Hanmo Chen, Hengman Zhu, Rui Du, Shanliang Qian, Shuai Liu, Weijun Hong, Jinke He, Yibing Zhang, Liang Zhao, Clare Zhu, Julian Togelius, Sharada P. Mohanty, Jiaxin Chen, Xiu Li, Xiaolong Zhu, Phillip Isola
2023 J jnl
Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMO.
CoRR
Yangkun Chen, Joseph Suarez, Junjie Zhang, ChengHui Yu, Bo Wu, Hanmo Chen, Hengman Zhu, Rui Du, Shanliang Qian, Shuai Liu, Weijun Hong, Jinke He, Yibing Zhang, Liang Zhao, Clare Zhu, Julian Togelius, Sharada P. Mohanty, Jiaxin Chen, Xiu Li, Xiaolong Zhu, Phillip Isola
2023 J jnl
The NeurIPS 2022 Neural MMO Challenge: A Massively Multiagent Competition with Specialization and Trade.
CoRR
Enhong Liu, Joseph Suarez, Chenhui You, Bo Wu, Bingcheng Chen, Jun Hu, Jiaxin Chen, Xiaolong Zhu, Clare Zhu, Julian Togelius, Sharada P. Mohanty, Weijun Hong, Rui Du, Yibing Zhang, Qinwen Wang, Xinhang Li, Zheng Yuan, Xiang Li, Yuejia Huang, Kun Zhang, Hanhui Yang, Shiqi Tang, Phillip Isola
2023 J jnl
The Sound Demixing Challenge 2023 - Cinematic Demixing Track.
CoRR
Stefan Uhlich, Giorgio Fabbro, Masato Hirano, Shusuke Takahashi, Gordon Wichern, Jonathan Le Roux, Dipam Chakraborty, Sharada P. Mohanty, Kai Li, Yi Luo, Jianwei Yu, Rongzhi Gu, Roman A. Solovyev, Alexander L. Stempkovskiy, Tatiana Habruseva, Mikhail Sukhovei, Yuki Mitsufuji
2023 J jnl
The Sound Demixing Challenge 2023 - Music Demixing Track.
CoRR
Giorgio Fabbro, Stefan Uhlich, Chieh-Hsin Lai, Woosung Choi, Marco A. Martínez Ramírez, Wei-Hsiang Liao, Igor Gadelha, Geraldo Ramos, Eddie Hsu, Hugo Rodrigues, Fabian-Robert Stöter, Alexandre Défossez, Yi Luo, Jianwei Yu, Dipam Chakraborty, Sharada P. Mohanty, Roman A. Solovyev, Alexander L. Stempkovskiy, Tatiana Habruseva, Nabarun Goswami, Tatsuya Harada, Minseok Kim, Jun Hyung Lee, Yuanliang Dong, Xinran Zhang, Jiafeng Liu, Yuki Mitsufuji
2023 J jnl
Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition.
CoRR
Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Sharada P. Mohanty, Byron Galbraith, Ke Chen, Yan Song, Tianze Zhou, Bingquan Yu, He Liu, Kai Guan, Yujing Hu, Tangjie Lv, Federico Malato, Florian Leopold, Amogh Raut, Ville Hautamäki, Andrew Melnik, Shu Ishida, João F. Henriques, Robert Klassert, Walter Laurito, Ellen R. Novoseller, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins, Josh Miller, Rohin Shah
2022 J jnl
Insights From the NeurIPS 2021 NetHack Challenge.
CoRR
Eric Hambro, Sharada P. Mohanty, Dmitrii Babaev, Minwoo Byeon, Dipam Chakraborty, Edward Grefenstette, Minqi Jiang, DaeJin Jo, Anssi Kanervisto, Jongmin Kim, Sungwoong Kim, Robert Kirk, Vitaly Kurin, Heinrich Küttler, Taehwon Kwon, Donghoon Lee, Vegard Mella, Nantas Nardelli, Ivan Nazarov, Nikita Ovsov, Jack Parker-Holder, Roberta Raileanu, Karolis Ramanauskas, Tim Rocktäschel, Danielle Rothermel, Mikayel Samvelyan, Dmitry Sorokin, Maciej Sypetkowski, Michal Sypetkowski
2021 J jnl
Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World.
CoRR
Florian Laurent, Manuel Schneider, Christian Scheller, Jeremy D. Watson, Jiaoyang Li, Zhe Chen, Yi Zheng, Shao-Hung Chan, Konstantin Makhnev, Oleg Svidchenko, Vladimir Egorov, Dmitry Ivanov, Aleksei Shpilman, Evgenija Spirovska, Oliver Tanevski, Aleksandar Nikov, Ramon Grunder, David Galevski, Jakov Mitrovski, Guillaume Sartoretti, Zhiyao Luo, Mehul Damani, Nilabha Bhattacharya, Shivam Agarwal, Adrian Egli, Erik Nygren, Sharada P. Mohanty
2021 — conf
Insights From the NeurIPS 2021 NetHack Challenge.
NeurIPS (Competition and Demos)
Eric Hambro, Sharada P. Mohanty, Dmitrii Babaev, Minwoo Byeon, Dipam Chakraborty, Edward Grefenstette, Minqi Jiang, DaeJin Jo, Anssi Kanervisto, Jongmin Kim, Sungwoong Kim, Robert Kirk, Vitaly Kurin, Heinrich Küttler, Taehwon Kwon, Donghoon Lee, Vegard Mella, Nantas Nardelli, Ivan Nazarov, Nikita Ovsov, Jack Parker-Holder, Roberta Raileanu, Karolis Ramanauskas, Tim Rocktäschel, Danielle Rothermel, Mikayel Samvelyan, Dmitry Sorokin, Maciej Sypetkowski, Michal Sypetkowski
2021 J jnl
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark.
CoRR
Sharada P. Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Grazvydas Semetulskis, João Schapke, Jonas Kubilius, Jurgis Pasukonis, Linas Klimas, Matthew J. Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe
2021 J jnl
Supervised Learning Computer Vision Benchmark for Snake Species Identification From Photographs: Implications for Herpetology and Global Health.
Frontiers Artif. Intell.
Andrew Durso, Moorthy Gokula Krishnan, Sharada P. Mohanty, Isabelle Bolon, Marcel Salathé, Rafael Luis Ruiz De Castaneda
2021 — conf
The CityLearn Challenge 2022: Overview, Results, and Lessons Learned.
NeurIPS (Competition and Demos)
Kingsley Nweye, Zoltán Nagy, Sharada P. Mohanty, Dipam Chakraborty, Siva Sankaranarayanan, Tianzhen Hong, Sourav Dey, Gregor Henze, Ján Drgona, Fangquan Lin, Wei Jiang, Hanwei Zhang, Zhongkai Yi, Jihai Zhang, Cheng Yang, Matthew Motoki, Sorapong Khongnawang, Michael Ibrahim, Abilmansur Zhumabekov, Daniel May, Zhihu Yang, Xiaozhuang Song, Han Zhang, Xiaoning Dong, Shun Zheng, Jiang Bian
2021 J jnl
The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors.
CoRR
William H. Guss, Mario Ynocente Castro, Sam Devlin, Brandon Houghton, Noboru Sean Kuno, Crissman Loomis, Stephanie Milani, Sharada P. Mohanty, Keisuke Nakata, Ruslan Salakhutdinov, John Schulman, Shinya Shiroshita, Nicholay Topin, Avinash Ummadisingu, Oriol Vinyals
2021 J jnl
The MineRL BASALT Competition on Learning from Human Feedback.
CoRR
Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, Pieter Abbeel, Stuart Russell, Anca D. Dragan
2021 — conf
The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions.
NeurIPS Datasets and Benchmarks
Jennifer J. Sun, Tomomi Karigo, Dipam Chakraborty, Sharada P. Mohanty, Benjamin Wild, Quan Sun, Chen Chen, David J. Anderson, Pietro Perona, Yisong Yue, Ann Kennedy
2021 J jnl
The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions.
CoRR
Jennifer J. Sun, Tomomi Karigo, Dipam Chakraborty, Sharada P. Mohanty, David J. Anderson, Pietro Perona, Yisong Yue, Ann Kennedy
2021 — conf
The NeurIPS 2022 Neural MMO Challenge: A Massively Multiagent Competition with Specialization and Trade.
NeurIPS (Competition and Demos)
Enhong Liu, Joseph Suarez, Chenhui You, Bo Wu, Bingcheng Chen, Jun Hu, Jiaxin Chen, Xiaolong Zhu, Clare Zhu, Julian Togelius, Sharada P. Mohanty, Weijun Hong, Rui Du, Yibing Zhang, Qinwen Wang, Xinhang Li, Zheng Yuan, Xiang Li, Yuejia Huang, Kun Zhang, Hanhui Yang, Shiqi Tang, Phillip Isola
2021 — conf
Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition.
NeurIPS (Competition and Demos)
Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff, Brandon Houghton, Sharada P. Mohanty, Byron Galbraith, Ke Chen, Yan Song, Tianze Zhou, Bingquan Yu, He Liu, Kai Guan, Yujing Hu, Tangjie Lv, Federico Malato, Florian Leopold, Amogh Raut, Ville Hautamäki, Andrew Melnik, Shu Ishida, João F. Henriques, Robert Klassert, Walter Laurito, Lucas Cazzonelli, Cedric Kulbach, Nicholas Popovic, Marvin Schweizer, Ellen R. Novoseller, Vinicius G. Goecks, Nicholas R. Waytowich, David Watkins, Josh Miller, Rohin Shah
2021 J jnl
Towards robust and domain agnostic reinforcement learning competitions.
CoRR
William Hebgen Guss, Stephanie Milani, Nicholay Topin, Brandon Houghton, Sharada P. Mohanty, Andrew Melnik, Augustin Harter, Benoit Buschmaas, Bjarne Jaster, Christoph Berganski, Dennis Heitkamp, Marko Henning, Helge J. Ritter, Chengjie Wu, Xiaotian Hao, Yiming Lu, Hangyu Mao, Yihuan Mao, Chao Wang, Michal Opanowicz, Anssi Kanervisto, Yanick Schraner, Christian Scheller, Xiren Zhou, Lu Liu, Daichi Nishio, Toi Tsuneda, Karolis Ramanauskas, Gabija Juceviciute
2020 — conf
Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World.
NeurIPS (Competition and Demos)
Florian Laurent, Manuel Schneider, Christian Scheller, Jeremy D. Watson, Jiaoyang Li, Zhe Chen, Yi Zheng, Shao-Hung Chan, Konstantin Makhnev, Oleg Svidchenko, Vladimir Egorov, Dmitry Ivanov, Aleksei Shpilman, Evgenija Spirovska, Oliver Tanevski, Aleksandar Nikov, Ramon Grunder, David Galevski, Jakov Mitrovski, Guillaume Sartoretti, Zhiyao Luo, Mehul Damani, Nilabha Bhattacharya, Shivam Agarwal, Adrian Egli, Erik Nygren, Sharada P. Mohanty
2020 — conf
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark.
NeurIPS (Competition and Demos)
Sharada P. Mohanty, Jyotish Poonganam, Adrien Gaidon, Andrey Kolobov, Blake Wulfe, Dipam Chakraborty, Grazvydas Semetulskis, João Schapke, Jonas Kubilius, Jurgis Pasukonis, Linas Klimas, Matthew J. Hausknecht, Patrick MacAlpine, Quang Nhat Tran, Thomas Tumiel, Xiaocheng Tang, Xinwei Chen, Christopher Hesse, Jacob Hilton, William Hebgen Guss, Sahika Genc, John Schulman, Karl Cobbe
2020 J jnl
Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning.
CoRR
Stephanie Milani, Nicholay Topin, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Keisuke Nakata, Oriol Vinyals, Noboru Sean Kuno
2020 — conf
Towards robust and domain agnostic reinforcement learning competitions: MineRL 2020.
NeurIPS (Competition and Demos)
William Hebgen Guss, Stephanie Milani, Nicholay Topin, Brandon Houghton, Sharada P. Mohanty, Andrew Melnik, Augustin Harter, Benoit Buschmaas, Bjarne Jaster, Christoph Berganski, Dennis Heitkamp, Marko Henning, Helge J. Ritter, Chengjie Wu, Xiaotian Hao, Yiming Lu, Hangyu Mao, Yihuan Mao, Chao Wang, Michal Opanowicz, Anssi Kanervisto, Yanick Schraner, Christian Scheller, Xiren Zhou, Lu Liu, Daichi Nishio, Toi Tsuneda, Karolis Ramanauskas, Gabija Juceviciute
2019 — conf
Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning.
NeurIPS (Competition and Demos)
Stephanie Milani, Nicholay Topin, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Keisuke Nakata, Oriol Vinyals, Noboru Sean Kuno
2019 J jnl
The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors.
CoRR
William H. Guss, Cayden R. Codel, Katja Hofmann, Brandon Houghton, Noburu Kuno, Stephanie Milani, Sharada P. Mohanty, Diego Perez Liebana, Ruslan Salakhutdinov, Nicholay Topin, Manuela Veloso, Phillip Wang
2018 J jnl
Adversarial Vision Challenge.
CoRR
Wieland Brendel, Jonas Rauber, Alexey Kurakin, Nicolas Papernot, Behar Veliqi, Marcel Salathé, Sharada P. Mohanty, Matthias Bethge
2018 J jnl
Learning to Recognize Musical Genre from Audio.
CoRR
Michaël Defferrard, Sharada P. Mohanty, Sean F. Carroll, Marcel Salathé
2018 — conf
Learning to Recognize Musical Genre from Audio: Challenge Overview.
WWW (Companion Volume)
Michaël Defferrard, Sharada P. Mohanty, Sean F. Carroll, Marcel Salathé
2018 J jnl
Learning to Run challenge: Synthesizing physiologically accurate motion using deep reinforcement learning.
CoRR
Lukasz Kidzinski, Sharada P. Mohanty, Carmichael F. Ong, Jennifer L. Hicks, Sean F. Carroll, Sergey Levine, Marcel Salathé, Scott L. Delp
2016 J jnl
CCLTracker Framework: Monitoring user learning and activity in web based citizen science projects.
Hum. Comput.
Jose Luis Fernandez-Marquez, Ioannis Charalampidis, Oula Abu-Amsha, François Grey, Daniel K. Schneider, Ben Segal, Sharada P. Mohanty