• [2020] Rameshwar Pratap, Anup Deshmukh, Pratheeksha Nair, Anirudh Ravi, “Scaling up Simhash”, In the Proceeding of Machine Learning Research (ACML 2020)(Paper)

  • [2020] Yue Li, Pratheeksha Nair, Zhi Wen, Imane Chafi, et al, “Global Surveillance of COVID-19 by mining news media using a multi-source dynamic embedded topic model”, ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB 2020)

  • [2020] Arnab Kumar Mondal, Pratheeksha Nair, Kaleem Siddiqi, “Group Equivariant Deep Reinforcement Learning”, Inductive Biases, Invariances and Generalization in RL (ICML 2020)(Paper)

  • [2020] Yue Li, Pratheeksha Nair, Xing Han Lu, Zhi Wen, et al, “Inferring multimodal latent topics from electronic health records”, Nature Communications volume 11, Article number: 2536 (2020) (Paper)

  • [2018] Pratheeksha Nair, Anup Anand Deshmukh, Dr. Shrisha Rao, “A Scalable Clustering Algorithm for Serendipity in Recommender Systems”, Workshop Proceedings of IEEE ICDM - ICDM 2018 (Paper)(Code)

  • [2018] Dr. Rameshwar Pratap, Pratheeksha Nair, Anup Anand Deshmukh, Tarun Dutt, “A Faster Sampling Algorithm for Spherical k-Means”, Proceedings of Machine Learning Research (PMLR) - ACML 2018(Paper)(Code)

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