Preprints

  • Maximum Reward Formulation In Reinforcement Learning.
    Sai Krishna Gottipati, Yashaswi Pathak, Rohan Nuttall, Raviteja Chunduru, Ahmed Touati, Sriram Ganapathi Subramanian, Matthew E Taylor, Sarath Chandar.
    In arXiv, 2020.
    [arXiv]

  • MLMLM: Link Prediction with Mean Likelihood Masked Language Model.
    Louis Clouatre, Philippe Trempe, Amal Zouaq, Sarath Chandar.
    In arXiv, 2020.
    [arXiv]

  • How To Evaluate Your Dialogue System: Probe Tasks as an Alternative for Token-level Evaluation Metrics.
    Prasanna Parthasarathi, Joelle Pineau, Sarath Chandar.
    In arXiv, 2020.
    [arXiv], [code]

  • PatchUp: A Regularization Technique for Convolutional Neural Networks.
    Mojtaba Faramarzi, Mohammad Amini, Akilesh Badrinaaraayanan, Vikas Verma, Sarath Chandar.
    In arXiv, 2020.
    [arXiv], [code]

Conference and Journal Papers

2020

  1. 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]

  2. 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]