Anuvaad Pranaali: A RESTful API for Machine Translation. - Nehal J. Wani; Sharada Prasanna Mohanty; Suresh Purini; Dipti Misra Sharma (ICSOC Workshops, 2016)

Kathaa: A Visual Programming Framework for NLP Applications. - Sharada Prasanna Mohanty; Nehal J. Wani; Manish Shrivastava 001; Dipti Misra Sharma (HLT-NAACL Demos, 2016)

Kathaa : NLP Systems as Edge-Labeled Directed Acyclic MultiGraphs. - Sharada Prasanna Mohanty; Nehal J. Wani; Manish Srivastava; Dipti Misra Sharma (WLSI/OIAF4HLT@COLING, 2016)

Using Deep Learning for Image-Based Plant Disease Detection. - Sharada Prasanna Mohanty; David P. Hughes; Marcel Salathé (CoRR, 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)

Learning to Recognize Musical Genre from Audio: Challenge Overview. - Michaël Defferrard; Sharada P. Mohanty; Sean F. Carroll; Marcel Salathé (WWW (Companion Volume), 2018)

Learning to Recognize Musical Genre from Audio. - Michaël Defferrard; Sharada P. Mohanty; Sean F. Carroll; Marcel Salathé (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 Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments. - Lukasz Kidzinski; Sharada Prasanna Mohanty; Carmichael F. Ong; Zhewei Huang; Shuchang Zhou 001; Anton Pechenko; Adam Stelmaszczyk; Piotr Jarosik; Mikhail Pavlov; Sergey Kolesnikov; Sergey M. Plis; Zhibo Chen 001; et al. (CoRR, 2018)

Adversarial Vision Challenge. - Wieland Brendel; Jonas Rauber; Alexey Kurakin; Nicolas Papernot; Behar Veliqi; Marcel Salathé; Sharada P. Mohanty; Matthias Bethge (CoRR, 2018)

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 (NeurIPS (Competition and Demos), 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)

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 021; Rongzhong Lian; Hao Tian 005; Wojciech Jaskowski; Garrett Andersen; et al. (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)

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)

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; et al. (NeurIPS (Competition and Demos), 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 001; Zhe Chen 016; Yi Zheng; Shao-Hung Chan; Konstantin Makhnev; Oleg Svidchenko; Vladimir Egorov; Dmitry Ivanov; et al. (NeurIPS (Competition and Demos), 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; et al. (NeurIPS (Competition and Demos), 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; et al. (CoRR, 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; et al. (Frontiers Artif. Intell., 2020)

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 006; Sungwoong Kim; Robert Kirk; et al. (NeurIPS (Competition and Demos), 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 014; Jiaxin Chen; Xiaolong Zhu; Clare Zhu; Julian Togelius; Sharada P. Mohanty; Weijun Hong; et al. (NeurIPS (Competition and Demos), 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; et al. (NeurIPS (Competition and Demos), 2021)

The CityLearn Challenge 2022: Overview, Results, and Lessons Learned. - Kingsley Nweye; Zoltán Nagy 002; Sharada P. Mohanty; Dipam Chakraborty; Siva Sankaranarayanan; Tianzhen Hong; Sourav Dey; Gregor Henze; Ján Drgona; Fangquan Lin; Wei Jiang 027; Hanwei Zhang 002; et al. (NeurIPS (Competition and Demos), 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 (NeurIPS Datasets and Benchmarks, 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; et al. (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)

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; et al. (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)

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 001; et al. (CoRR, 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)

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; et al. (AAMAS, 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; et al. (CoRR, 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 004; Jianwei Yu 001; Rongzhi Gu; et al. (CoRR, 2023)

The Sound Demixing Challenge 2023 - Music Demixing Track. - Giorgio Fabbro; Stefan Uhlich; Chieh-Hsin Lai; Woosung Choi; Marco A. Martínez Ramírez; Wei-Hsiang Liao 001; Igor Gadelha; Geraldo Ramos; Eddie Hsu; Hugo Rodrigues; Fabian-Robert Stöter; Alexandre Défossez; et al. (Trans. Int. Soc. Music. Inf. Retr., 2024)