Sharada P. Mohanty

According to our database, Sharada P. Mohanty authored at least 35 papers between 2016 and 2024.

Collaborative distances:

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

2024

The Sound Demixing Challenge 2023 - Music Demixing Track.

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

Trans. Int. Soc. Music. Inf. Retr., January, 2024

2023

The Sound Demixing Challenge 2023 - Cinematic Demixing Track.

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

CoRR, 2023

Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition.

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

CoRR, 2023

Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMO.

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

Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023

2021

Supervised Learning Computer Vision Benchmark for Snake Species Identification From Photographs: Implications for Herpetology and Global Health.

Andrew Durso, Moorthy Gokula Krishnan, Sharada P. Mohanty, Isabelle Bolon, Marcel Salathé, Rafael Luis Ruiz De Castaneda

Frontiers Artif. Intell., 2021

The MineRL BASALT Competition on Learning from Human Feedback.

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

CoRR, 2021

The Food Recognition Benchmark: Using DeepLearning to Recognize Food on Images.

Sharada Prasanna Mohanty, Gaurav Singhal, Eric Antoine Scuccimarra, Djilani Kebaili, Harris Héritier, Victor Boulanger, Marcel Salathé

CoRR, 2021

Towards robust and domain agnostic reinforcement learning competitions.

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

CoRR, 2021

The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions.

Jennifer J. Sun, Tomomi Karigo, Dipam Chakraborty, Sharada P. Mohanty, David J. Anderson, Pietro Perona, Yisong Yue, Ann Kennedy

CoRR, 2021

The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors.

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

CoRR, 2021

The Multi-Agent Behavior Dataset: Mouse Dyadic Social Interactions.

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

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

The CityLearn Challenge 2022: Overview, Results, and Lessons Learned.

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

Proceedings of the NeurIPS 2022 Competition Track, 2021

Towards Solving Fuzzy Tasks with Human Feedback: A Retrospective of the MineRL BASALT 2022 Competition.

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

Proceedings of the NeurIPS 2022 Competition Track, 2021

The NeurIPS 2022 Neural MMO Challenge: A Massively Multiagent Competition with Specialization and Trade.

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

Proceedings of the NeurIPS 2022 Competition Track, 2021

Insights From the NeurIPS 2021 NetHack Challenge.

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

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

2020

Deep Learning for Understanding Satellite Imagery: An Experimental Survey.

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

Frontiers Artif. Intell., 2020

Flatland-RL : Multi-Agent Reinforcement Learning on Trains.

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

CoRR, 2020

Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark.

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

Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020

Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World.

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

Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020

Towards robust and domain agnostic reinforcement learning competitions: MineRL 2020.

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

Proceedings of the NeurIPS 2020 Competition and Demonstration Track, 2020

2019

Investment Ranking Challenge: Identifying the best performing stocks based on their semi-annual returns.

Shanka Subhra Mondal, Sharada Prasanna Mohanty, Benjamin Harlander, Mehmet Köseoglu, Lance Rane, Kirill Romanov, Wei-Kai Liu, Pranoot Hatwar, Marcel Salathé, Joe Byrum

CoRR, 2019

The MineRL Competition on Sample Efficient Reinforcement Learning using Human Priors.

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

CoRR, 2019

Artificial Intelligence for Prosthetics - challenge solutions.

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

CoRR, 2019

The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition.

Diego Pérez-Liébana, Katja Hofmann, Sharada Prasanna Mohanty, Noburu Kuno, André Kramer, Sam Devlin, Raluca D. Gaina, Daniel Ionita

CoRR, 2019

Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning.

Stephanie Milani, Nicholay Topin, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Keisuke Nakata, Oriol Vinyals, Noboru Sean Kuno

Proceedings of the NeurIPS 2019 Competition and Demonstration Track, 2019

2018

Adversarial Vision Challenge.

Wieland Brendel, Jonas Rauber, Alexey Kurakin, Nicolas Papernot, Behar Veliqi, Marcel Salathé, Sharada P. Mohanty, Matthias Bethge

CoRR, 2018

Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments.

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

CoRR, 2018

Learning to Run challenge: Synthesizing physiologically accurate motion using deep reinforcement learning.

Lukasz Kidzinski, Sharada P. Mohanty, Carmichael F. Ong, Jennifer L. Hicks, Sean F. Carroll, Sergey Levine, Marcel Salathé, Scott L. Delp

CoRR, 2018

Learning to Recognize Musical Genre from Audio.

Michaël Defferrard, Sharada P. Mohanty, Sean F. Carroll, Marcel Salathé

CoRR, 2018

Learning to Recognize Musical Genre from Audio: Challenge Overview.

Michaël Defferrard, Sharada P. Mohanty, Sean F. Carroll, Marcel Salathé

Proceedings of the Companion of the The Web Conference 2018 on The Web Conference 2018, 2018

2016

CCLTracker Framework: Monitoring user learning and activity in web based citizen science projects.

Jose Luis Fernandez-Marquez, Ioannis Charalampidis, Oula Abu-Amsha, François Grey, Daniel K. Schneider, Ben Segal, Sharada P. Mohanty

Hum. Comput., 2016

Using Deep Learning for Image-Based Plant Disease Detection.

Sharada Prasanna Mohanty, David P. Hughes, Marcel Salathé

CoRR, 2016

Kathaa : NLP Systems as Edge-Labeled Directed Acyclic MultiGraphs.

Sharada Prasanna Mohanty, Nehal J. Wani, Manish Srivastava, Dipti Misra Sharma

Proceedings of the Third International Workshop on Worldwide Language Service Infrastructure and Second Workshop on Open Infrastructures and Analysis Frameworks for Human Language Technologies WLSI/OIAF4HLT@COLING, 2016

Kathaa: A Visual Programming Framework for NLP Applications.

Sharada Prasanna Mohanty, Nehal J. Wani, Manish Shrivastava, Dipti Misra Sharma

Proceedings of the Demonstrations Session, 2016

Anuvaad Pranaali: A RESTful API for Machine Translation.

Nehal J. Wani, Sharada Prasanna Mohanty, Suresh Purini, Dipti Misra Sharma

Proceedings of the Service-Oriented Computing - ICSOC 2016 Workshops, 2016