ADAAPT: A Deep Architecture for Adaptive Policy Transfer from Multiple Sources. - Janarthanan Rajendran; P. Prasanna; Balaraman Ravindran; Mitesh M. Khapra (CoRR, 2015)

A Correlational Encoder Decoder Architecture for Pivot Based Sequence Generation. - Amrita Saha; Mitesh M. Khapra; Sarath Chandar; Janarthanan Rajendran; Kyunghyun Cho (COLING, 2016)

Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning. - Janarthanan Rajendran; Mitesh M. Khapra; Sarath Chandar; Balaraman Ravindran (HLT-NAACL, 2016)

Attend, Adapt and Transfer: Attentive Deep Architecture for Adaptive Transfer from multiple sources in the same domain. - Janarthanan Rajendran; Aravind S. Lakshminarayanan; Mitesh M. Khapra; P. Prasanna; Balaraman Ravindran (ICLR (Poster), 2017)

Learning End-to-End Goal-Oriented Dialog with Multiple Answers. - Janarthanan Rajendran; Jatin Ganhotra; Satinder Singh 001; Lazaros Polymenakos (EMNLP, 2018)

Named Entities troubling your Neural Methods? Build NE-Table: A neural approach for handling Named Entities. - Janarthanan Rajendran; Jatin Ganhotra; Xiaoxiao Guo; Mo Yu; Satinder Singh 001 (CoRR, 2018)

Discovery of Useful Questions as Auxiliary Tasks. - Vivek Veeriah; Matteo Hessel; Zhongwen Xu; Janarthanan Rajendran; Richard L. Lewis; Junhyuk Oh; Hado van Hasselt; David Silver; Satinder Singh 001 (NeurIPS, 2019)

NE-Table: A Neural key-value table for Named Entities. - Janarthanan Rajendran; Jatin Ganhotra; Xiaoxiao Guo; Mo Yu; Satinder Singh 001; Lazaros Polymenakos (RANLP, 2019)

Learning End-to-End Goal-Oriented Dialog with Maximal User Task Success and Minimal Human Agent Use. - Janarthanan Rajendran; Jatin Ganhotra; Lazaros C. Polymenakos (Trans. Assoc. Comput. Linguistics, 2019)

How Should an Agent Practice? - Janarthanan Rajendran; Richard L. Lewis; Vivek Veeriah; Honglak Lee; Satinder Singh 001 (AAAI, 2020)

Quantifying the Effects of COVID-19 on Mental Health Support Forums. - Laura Biester; Katie Matton; Janarthanan Rajendran; Emily Mower Provost; Rada Mihalcea (NLP4COVID@EMNLP, 2020)

Meta-Learning Requires Meta-Augmentation. - Janarthanan Rajendran; Alexander Irpan; Eric Jang (NeurIPS, 2020)

Reinforcement Learning of Implicit and Explicit Control Flow Instructions. - Ethan Brooks; Janarthanan Rajendran; Richard L. Lewis; Satinder Singh 001 (ICML, 2021)

Learning to Learn End-to-End Goal-Oriented Dialog From Related Dialog Tasks. - Janarthanan Rajendran; Jonathan K. Kummerfeld; Satinder Singh 001 (CoRR, 2021)

Understanding the Impact of COVID-19 on Online Mental Health Forums. - Laura Biester; Katie Matton; Janarthanan Rajendran; Emily Mower Provost; Rada Mihalcea (ACM Trans. Manag. Inf. Syst., 2021)

On End-to-End Learning of Neural Goal-Oriented Dialog Systems. - Janarthanan Rajendran (2021)

Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods. - Yi Wan; Ali Rahimi-Kalahroudi; Janarthanan Rajendran; Ida Momennejad; Sarath Chandar; Harm van Seijen (ICML, 2022)

An Introduction to Lifelong Supervised Learning. - Shagun Sodhani; Mojtaba Faramarzi; Sanket Vaibhav Mehta; Pranshu Malviya; Mohamed A. Abdelsalam; Janarthanan Rajendran; Sarath Chandar (CoRR, 2022)

PatchBlender: A Motion Prior for Video Transformers. - Gabriele Prato 001; Yale Song; Janarthanan Rajendran; R. Devon Hjelm; Neel Joshi; Sarath Chandar (CoRR, 2022)

Dealing With Non-stationarity in Decentralized Cooperative Multi-Agent Deep Reinforcement Learning via Multi-Timescale Learning. - Hadi Nekoei; Akilesh Badrinaaraayanan; Amit Sinha; Mohammad Amini; Janarthanan Rajendran; Aditya Mahajan; Sarath Chandar (CoLLAs, 2023)

Towards Few-shot Coordination: Revisiting Ad-hoc Teamplay Challenge In the Game of Hanabi. - Hadi Nekoei; Xutong Zhao; Janarthanan Rajendran; Miao Liu; Sarath Chandar (CoLLAs, 2023)

Replay Buffer with Local Forgetting for Adapting to Local Environment Changes in Deep Model-Based Reinforcement Learning. - Ali Rahimi-Kalahroudi; Janarthanan Rajendran; Ida Momennejad; Harm van Seijen; Sarath Chandar (CoLLAs, 2023)

Conditionally optimistic exploration for cooperative deep multi-agent reinforcement learning. - Xutong Zhao; Yangchen Pan; Chenjun Xiao; Sarath Chandar; Janarthanan Rajendran (UAI, 2023)

Replay Buffer With Local Forgetting for Adaptive Deep Model-Based Reinforcement Learning. - Ali Rahimi-Kalahroudi; Janarthanan Rajendran; Ida Momennejad; Harm van Seijen; Sarath Chandar (CoRR, 2023)

Language Model-In-The-Loop: Data Optimal Approach to Learn-To-Recommend Actions in Text Games. - Arjun Vaithilingam Sudhakar; Prasanna Parthasarathi; Janarthanan Rajendran; Sarath Chandar (CoRR, 2023)

Intelligent Switching for Reset-Free RL. - Darshan Patil; Janarthanan Rajendran; Glen Berseth; Sarath Chandar (ICLR, 2024)

Mastering Memory Tasks with World Models. - Mohammad Reza Samsami; Artem Zholus; Janarthanan Rajendran; Sarath Chandar (ICLR, 2024)

Toward Debugging Deep Reinforcement Learning Programs with RLExplorer. - Rached Bouchoucha; Ahmed Haj Yahmed; Darshan Patil; Janarthanan Rajendran; Amin Nikanjam; Sarath Chandar; Foutse Khomh (ICSME, 2024)

Balancing Context Length and Mixing Times for Reinforcement Learning at Scale. - Matthew Riemer; Khimya Khetarpal; Janarthanan Rajendran; Sarath Chandar (NeurIPS, 2024)

Fairness Incentives in Response to Unfair Dynamic Pricing. - Jesse Thibodeau; Hadi Nekoei; Afaf Taïk; Janarthanan Rajendran; Golnoosh Farnadi (CoRR, 2024)

Defending against Reverse Preference Attacks is Difficult. - Domenic Rosati; Giles Edkins; Harsh Raj; David Atanasov; Subhabrata Majumdar; Janarthanan Rajendran; Frank Rudzicz; Hassan Sajjad 001 (CoRR, 2024)

A Generalist Hanabi Agent. - Arjun Vaithilingam Sudhakar; Hadi Nekoei; Mathieu Reymond; Miao Liu; Janarthanan Rajendran; Sarath Chandar (ICLR, 2025)

Balancing Profit and Fairness in Risk-Based Pricing Markets. - Jesse Thibodeau; Hadi Nekoei; Afaf Taïk; Janarthanan Rajendran; Golnoosh Farnadi (CoRR, 2025)