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ORCIDSharada P. Mohanty
Sharada Prasanna Mohanty
Person information
- affiliation: École Polytechnique Fédérale de Lausanne (EPFL), Switzerland
- affiliation: International Institute of Information Technology, Hyderabad, Language Technology Research Center, India
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Journal Articles
- 2024
[j4]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:
The Sound Demixing Challenge 2023 - Music Demixing Track. Trans. Int. Soc. Music. Inf. Retr. 7(1): 63-84 (2024)- 2021
- [j3]Andrew Durso, Moorthy Gokula Krishnan, Sharada P. Mohanty, Isabelle Bolon, Marcel Salathé, Rafael Luis Ruiz De Castaneda:
Supervised Learning Computer Vision Benchmark for Snake Species Identification From Photographs: Implications for Herpetology and Global Health. Frontiers Artif. Intell. 4: 582110 (2021) - 2020
- [j2]Sharada Prasanna Mohanty, Jakub Czakon, Kamil A. Kaczmarek, Andrzej Pyskir, Piotr Tarasiewicz, Saket Kunwar, Janick Rohrbach, Dave Luo, Manjunath Prasad, Sascha Fleer, Jan Philip Göpfert, Akshat Tandon, Guillaume Mollard, Nikhil Rayaprolu, Marcel Salathé, Malte Schilling:
Deep Learning for Understanding Satellite Imagery: An Experimental Survey. Frontiers Artif. Intell. 3: 534696 (2020) - 2016
- [j1]Jose Luis Fernandez-Marquez, Ioannis Charalampidis, Oula Abu-Amsha, François Grey, Daniel K. Schneider, Ben Segal, Sharada P. Mohanty:
CCLTracker Framework: Monitoring user learning and activity in web based citizen science projects. Hum. Comput. 3(1): 99-117 (2016)
Conference and Workshop Papers
- 2023
- [c14]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:
Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMO. AAMAS 2023: 2490-2492 - 2021
- [c13]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:
The NeurIPS 2022 Neural MMO Challenge: A Massively Multiagent Competition with Specialization and Trade. NeurIPS (Competition and Demos) 2021: 18-34 - [c12]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:
Insights From the NeurIPS 2021 NetHack Challenge. NeurIPS (Competition and Demos) 2021: 41-52 - [c11]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:
The CityLearn Challenge 2022: Overview, Results, and Lessons Learned. NeurIPS (Competition and Demos) 2021: 85-103 - [c10]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:
Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition. NeurIPS (Competition and Demos) 2021: 171-188 - [c9]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:
The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions. NeurIPS Datasets and Benchmarks 2021 - 2020
- [c8]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:
Towards robust and domain agnostic reinforcement learning competitions: MineRL 2020. NeurIPS (Competition and Demos) 2020: 233-252 - [c7]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:
Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World. NeurIPS (Competition and Demos) 2020: 275-301 - [c6]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:
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. NeurIPS (Competition and Demos) 2020: 361-395 - 2019
- [c5]Stephanie Milani, Nicholay Topin, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Keisuke Nakata, Oriol Vinyals, Noboru Sean Kuno:
Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning. NeurIPS (Competition and Demos) 2019: 203-214 - 2018
- [c4]Michaël Defferrard, Sharada P. Mohanty, Sean F. Carroll, Marcel Salathé:
Learning to Recognize Musical Genre from Audio: Challenge Overview. WWW (Companion Volume) 2018: 1921-1922 - 2016
- [c3]Nehal J. Wani, Sharada Prasanna Mohanty, Suresh Purini, Dipti Misra Sharma:
Anuvaad Pranaali: A RESTful API for Machine Translation. ICSOC Workshops 2016: 179-183 - [c2]Sharada Prasanna Mohanty, Nehal J. Wani, Manish Shrivastava, Dipti Misra Sharma:
Kathaa: A Visual Programming Framework for NLP Applications. HLT-NAACL Demos 2016: 92-96 - [c1]Sharada Prasanna Mohanty, Nehal J. Wani, Manish Srivastava, Dipti Misra Sharma:
Kathaa : NLP Systems as Edge-Labeled Directed Acyclic MultiGraphs. WLSI/OIAF4HLT@COLING 2016: 1-10
Informal and Other Publications
- 2023
- [i24]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:
Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition. CoRR abs/2303.13512 (2023) - [i23]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:
The Sound Demixing Challenge 2023 - Music Demixing Track. CoRR abs/2308.06979 (2023) - [i22]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:
The Sound Demixing Challenge 2023 - Cinematic Demixing Track. CoRR abs/2308.06981 (2023) - [i21]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:
Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMO. CoRR abs/2308.15802 (2023) - [i20]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:
The NeurIPS 2022 Neural MMO Challenge: A Massively Multiagent Competition with Specialization and Trade. CoRR abs/2311.03707 (2023) - 2022
- [i19]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:
Insights From the NeurIPS 2021 NetHack Challenge. CoRR abs/2203.11889 (2022) - 2021
- [i18]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:
The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors. CoRR abs/2101.11071 (2021) - [i17]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:
Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark. CoRR abs/2103.15332 (2021) - [i16]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:
Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World. CoRR abs/2103.16511 (2021) - [i15]Jennifer J. Sun, Tomomi Karigo, Dipam Chakraborty, Sharada P. Mohanty, David J. Anderson, Pietro Perona, Yisong Yue, Ann Kennedy:
The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions. CoRR abs/2104.02710 (2021) - [i14]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:
Towards robust and domain agnostic reinforcement learning competitions. CoRR abs/2106.03748 (2021) - [i13]Sharada Prasanna Mohanty, Gaurav Singhal, Eric Antoine Scuccimarra, Djilani Kebaili, Harris Héritier, Victor Boulanger, Marcel Salathé:
The Food Recognition Benchmark: Using DeepLearning to Recognize Food on Images. CoRR abs/2106.14977 (2021) - [i12]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:
The MineRL BASALT Competition on Learning from Human Feedback. CoRR abs/2107.01969 (2021) - 2020
- [i11]Stephanie Milani, Nicholay Topin, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Keisuke Nakata, Oriol Vinyals, Noboru Sean Kuno:
Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning. CoRR abs/2003.05012 (2020) - [i10]Sharada Prasanna Mohanty, Erik Nygren, Florian Laurent, Manuel Schneider, Christian Scheller, Nilabha Bhattacharya, Jeremy D. Watson, Adrian Egli, Christian Eichenberger, Christian Baumberger, Gereon Vienken, Irene Sturm, Guillaume Sartoretti, Giacomo Spigler:
Flatland-RL : Multi-Agent Reinforcement Learning on Trains. CoRR abs/2012.05893 (2020) - 2019
- [i9]Diego Pérez-Liébana, Katja Hofmann, Sharada Prasanna Mohanty, Noburu Kuno, André Kramer, Sam Devlin, Raluca D. Gaina, Daniel Ionita:
The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition. CoRR abs/1901.08129 (2019) - [i8]Lukasz Kidzinski, Carmichael F. Ong, Sharada Prasanna Mohanty, Jennifer L. Hicks, Sean F. Carroll, Bo Zhou, Hong-cheng Zeng, Fan Wang, Rongzhong Lian, Hao Tian, Wojciech Jaskowski, Garrett Andersen, Odd Rune Lykkebø, Nihat Engin Toklu, Pranav Shyam, Rupesh Kumar Srivastava, Sergey Kolesnikov, Oleksii Hrinchuk, Anton Pechenko, Mattias Ljungström, Zhen Wang, Xu Hu, Zehong Hu, Minghui Qiu, Jun Huang, Aleksei Shpilman, Ivan Sosin, Oleg Svidchenko, Aleksandra Malysheva, Daniel Kudenko, Lance Rane, Aditya Bhatt, Zhengfei Wang, Penghui Qi, Zeyang Yu, Peng Peng, Quan Yuan, Wenxin Li, Yunsheng Tian, Ruihan Yang, Pingchuan Ma, Shauharda Khadka, Somdeb Majumdar, Zach Dwiel, Yinyin Liu, Evren Tumer, Jeremy D. Watson, Marcel Salathé, Sergey Levine, Scott L. Delp:
Artificial Intelligence for Prosthetics - challenge solutions. CoRR abs/1902.02441 (2019) - [i7]William H. Guss, Cayden Codel, Katja Hofmann, Brandon Houghton, Noburu Kuno, Stephanie Milani, Sharada P. Mohanty, Diego Perez Liebana, Ruslan Salakhutdinov, Nicholay Topin, Manuela Veloso, Phillip Wang:
The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors. CoRR abs/1904.10079 (2019) - [i6]Shanka Subhra Mondal, Sharada Prasanna Mohanty, Benjamin Harlander, Mehmet Köseoglu, Lance Rane, Kirill Romanov, Wei-Kai Liu, Pranoot Hatwar, Marcel Salathé, Joe Byrum:
Investment Ranking Challenge: Identifying the best performing stocks based on their semi-annual returns. CoRR abs/1906.08636 (2019) - 2018
- [i5]Michaël Defferrard, Sharada P. Mohanty, Sean F. Carroll, Marcel Salathé:
Learning to Recognize Musical Genre from Audio. CoRR abs/1803.05337 (2018) - [i4]Lukasz Kidzinski, Sharada P. Mohanty, Carmichael F. Ong, Jennifer L. Hicks, Sean F. Carroll, Sergey Levine, Marcel Salathé, Scott L. Delp:
Learning to Run challenge: Synthesizing physiologically accurate motion using deep reinforcement learning. CoRR abs/1804.00198 (2018) - [i3]Lukasz Kidzinski, Sharada Prasanna Mohanty, Carmichael F. Ong, Zhewei Huang, Shuchang Zhou, Anton Pechenko, Adam Stelmaszczyk, Piotr Jarosik, Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis, Zhibo Chen, Zhizheng Zhang, Jiale Chen, Jun Shi, Zhuobin Zheng, Chun Yuan, Zhihui Lin, Henryk Michalewski, Piotr Milos, Blazej Osinski, Andrew Melnik, Malte Schilling, Helge J. Ritter, Sean F. Carroll, Jennifer L. Hicks, Sergey Levine, Marcel Salathé, Scott L. Delp:
Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments. CoRR abs/1804.00361 (2018) - [i2]Wieland Brendel, Jonas Rauber, Alexey Kurakin, Nicolas Papernot, Behar Veliqi, Marcel Salathé, Sharada P. Mohanty, Matthias Bethge:
Adversarial Vision Challenge. CoRR abs/1808.01976 (2018) - 2016
- [i1]Sharada Prasanna Mohanty, David P. Hughes, Marcel Salathé:
Using Deep Learning for Image-Based Plant Disease Detection. CoRR abs/1604.03169 (2016)
Coauthor Index
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