Publications


Preprints


Conference and Journal Papers

  1. Continuous Coordination As a Realistic Scenario for Lifelong Learning.
    Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron Courville, Sarath Chandar.
    International Conference on Machine Learning (ICML), 2021.
    [arXiv], [code]

  2. MLMLM: Link Prediction with Mean Likelihood Masked Language Model.
    Louis Clouatre, Philippe Trempe, Amal Zouaq, Sarath Chandar.
    Findings of Association for Computational Linguistics (ACL), 2021.
    [arXiv]

  3. A Survey of Data Augmentation Approaches for NLP.
    Steven Y. Feng, Varun Gangal, Jason Wei, Sarath Chandar, Soroush Vosoughi, Teruko Mitamura, Eduard Hovy.
    Findings of Association for Computational Linguistics (ACL), 2021.
    [arXiv]

  4. IIRC: Incremental Implicitly-Refined Classification.
    Mohamed Abdelsalam, Mojtaba Faramarzi, Shagun Sodhani, Sarath Chandar.
    Conference on Computer Vision and Pattern Recognition (CVPR), 2021.
    [arXiv], [code], [website], [PyPI], [docs]

  5. Towered Actor Critic for Handling Multiple Action Types in Reinforcement Learning For Drug Discovery.
    Sai Krishna Gottipati, Yashaswi Pathak, Boris Sattarov, Sahir, Rohan Nuttall, Mohammad Amini, Matthew E. Taylor, Sarath Chandar.
    AAAI Conference on Artificial Intelligence, 2021.



  6. The LoCA Regret: A Consistent Metric to Evaluate Model-Based Behavior in Reinforcement Learning.
    Harm van Seijen, Hadi Nekoei, Evan Racah, Sarath Chandar.
    Neural Information Processing Systems (NeurIPS), 2020.
    [arXiv], [code]

  7. Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning.
    Sai Krishna Gottipati*, Boris Sattarov*, Sufeng Niu, Yashaswi Pathak, Haoran Wei, Shengchao Liu, Karam MJ Thomas,
    Simon Blackburn, Connor W Coley, Jian Tang, Sarath Chandar, Yoshua Bengio.
    International Conference on Machine Learning (ICML), 2020.
    [arXiv]

  8. The Hanabi Challenge: A New Frontier for AI Research.
    Nolan Bard*, Jakob N. Foerster*, Sarath Chandar, Neil Burch, Marc Lanctot, H. Francis Song, Emilio Parisotto, Vincent Dumoulin,
    Subhodeep Moitra, Edward Hughes, Iain Dunning, Shibl Mourad, Hugo Larochelle, Marc G. Bellemare, Michael Bowling.
    Artificial Intelligence Journal (AIJ), 2020.
    [arXiv], [code]

  9. Towards Training Recurrent Neural Networks for Lifelong Learning.
    Shagun Sodhani*, Sarath Chandar*, Yoshua Bengio.
    Neural Computation, 2020.
    [arXiv]


  10. Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study.
    Chinnadhurai Sankar, Sandeep Subramanian, Chris Pal, Sarath Chandar, Yoshua Bengio.
    Association for Computational Linguistics (ACL), 2019.
    [arXiv]

  11. Towards Lossless Encoding of Sentences.
    Gabriele Prato, Mathieu Duchesneau, Sarath Chandar, Alain Tapp.
    Association for Computational Linguistics (ACL), 2019.
    [arXiv]

  12. Towards Non-saturating Recurrent Units for Modelling Long-term Dependencies.
    Sarath Chandar*, Chinnadhurai Sankar*, Eugene Vorontsov, Samira Ebrahimi Kahou, Yoshua Bengio.
    Proceedings of AAAI, 2019.
    [arXiv], [code]

  13. Edge Replacement Grammars: A Formal Language Approach for Generating Graphs.
    Revanth Reddy*, Sarath Chandar*, Balaraman Ravindran.
    Proceedings of SIAM International Conference on Data Mining (SDM19), 2019.
    [arXiv]


  14. Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph.
    Amrita Saha, Vardaan Pahuja, Mitesh M. Khapra, Karthik Sankaranarayanan, Sarath Chandar.
    Proceedings of AAAI, 2018.
    [arXiv], [code/data]

  15. Dynamic Neural Turing Machine with Continuous and Discrete Addressing Schemes.
    Caglar Gulcehre, Sarath Chandar, Kyunghyun Cho, Yoshua Bengio.
    Neural Computation, 30(4): 857-884, 2018.
    [Initial version appeared in IJCAI Workshop on Deep Reinforcement Learning: Frontiers and Challenges, 2016].
    [arXiv]



  16. GuessWhat?! Visual object discovery through multi-modal dialogue.
    Harm de Vries, Florian Strub, Sarath Chandar, Olivier Pietquin, Hugo Larochelle, Aaron Courville.
    Proceedings of CVPR, 2017.
    [arXiv]



  17. A Correlational Encoder Decoder Architecture for Pivot Based Sequence Generation.
    Amrita Saha, Mitesh M Khapra, Sarath Chandar, Janarthanan Rajendran, Kyunghyun Cho.
    Proceedings of COLING, 2016.
    [arXiv]

  18. Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus.
    Iulian Vlad Serban, Alberto Garcia-Duran, Caglar Gulcehre, Sungjin Ahn, Sarath Chandar, Aaron Courville, Yoshua Bengio.
    Proceedings of ACL, 2016.
    [arXiv]

  19. Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning.
    Janarthanan Rajendran, Mitesh M Khapra, Sarath Chandar, Balaraman Ravindran.
    Proceedings of NAACL, 2016.
    [Initial version appeared in NIPS Workshop on Multimodal Machine Learning, 2015.]
    [arXiv]

  20. Correlational Neural Networks.
    Sarath Chandar, Mitesh M Khapra, Hugo Larochelle, Balaraman Ravindran.
    Neural Computation, 28(2): 286-304, 2016.
    [pdf][arXiv][code]



  21. From Multiple Views to Single View : A Neural Network Approach.
    Subendhu Rongali, Sarath Chandar, Ravindran B.
    Second ACM-IKDD Conference on Data Sciences, 2015.



  22. An Autoencoder Approach to Learning Bilingual Word Representations.
    Sarath Chandar, Stanislas Lauly, Hugo Larochelle, Mitesh M Khapra, Balaraman Ravindran, Vikas Raykar, Amrita Saha.
    Neural Information Processing Systems (NeurIPS), 2014.
    [pdf][Project Page][code]



Thesis


Workshop Papers and Technical Reports