Temporal Dynamics and Spatial Content in IoT Malware detection. - Ramnath Kumar; G. Geethakumari (TENCON, 2019)

eDarkFind: Unsupervised Multi-view Learning for Sybil Account Detection. - Ramnath Kumar; Shweta Yadav 001; Raminta Daniulaityte; Francois R. Lamy; Krishnaprasad Thirunarayan; Usha Lokala; Amit P. Sheth (WWW, 2020)

Rethinking Learning Dynamics in RL using Adversarial Networks. - Ramnath Kumar; Tristan Deleu; Yoshua Bengio (CoRR, 2022)

Look Back When Surprised: Stabilizing Reverse Experience Replay for Neural Approximation. - Ramnath Kumar; Dheeraj Nagaraj (CoRR, 2022)

The Effect of Diversity in Meta-Learning. - Ramnath Kumar; Tristan Deleu; Yoshua Bengio (AAAI, 2023)

On the Limits of Multi-modal Meta-Learning with Auxiliary Task Modulation Using Conditional Batch Normalization. - Jordi Armengol-Estapé; Vincent Michalski; Ramnath Kumar; Pierre-Luc St-Charles; Doina Precup; Samira Ebrahimi Kahou (CoRR, 2024)

EHI: End-to-end Learning of Hierarchical Index for Efficient Dense Retrieval. - Ramnath Kumar; Anshul Mittal; Nilesh Gupta; Aditya Kusupati; Inderjit S. Dhillon; Prateek Jain 002 (Trans. Mach. Learn. Res., 2024)

Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization. - Ramnath Kumar; Kushal Majmundar; Dheeraj Mysore Nagaraj; Arun Sai Suggala (Trans. Mach. Learn. Res., 2024)

Introspective Experience Replay: Look Back When Surprised. - Ramnath Kumar; Dheeraj Mysore Nagaraj (Trans. Mach. Learn. Res., 2024)