| Arduino based door unlocking system with real time control S Nath, P Banerjee, RN Biswas, SK Mitra, MK Naskar 2016 2nd International conference on contemporary computing and informatics …, 2016 | 56 | 2016 |
| Two-timescale networks for nonlinear value function approximation W Chung, S Nath, A Joseph, M White International Conference on Learning Representations (ICLR) 2019, 2019 | 42 | 2019 |
| Reinforcement learning for multi-product multi-node inventory management in supply chains NN Sultana, H Meisheri, V Baniwal, S Nath, B Ravindran, H Khadilkar arXiv preprint arXiv:2006.04037, 2020 | 27 | 2020 |
| Scalable multi-product inventory control with lead time constraints using reinforcement learning H Meisheri, NN Sultana, M Baranwal, V Baniwal, S Nath, S Verma, ... Neural Computing and Applications 34 (3), 1735-1757, 2022 | 25 | 2022 |
| Revisiting state augmentation methods for reinforcement learning with stochastic delays S Nath, M Baranwal, H Khadilkar Proceedings of the 30th ACM International Conference on Information …, 2021 | 17 | 2021 |
| Prioritizing samples in reinforcement learning with reducible loss S Sujit, S Nath, PHM Braga, SE Kahou Conference on Neural Information Processing Systems (NeurIPS), 2022 | 6 | 2022 |
| Smartphone camera‐based analysis of ELISA using artificial neural network S Nath, S Sarcar, B Chatterjee, R Chourashi, NS Chatterjee IET Computer Vision 12 (6), 826-833, 2018 | 6 | 2018 |
| Reinforcement learning for multi-product multi-node inventory management in supply chains. arXiv 2020 NN Sultana, H Meisheri, V Baniwal, S Nath, B Ravindran, H Khadilkar arXiv preprint arXiv:2006.04037, 2020 | 5 | 2020 |
| Training recurrent neural networks online by learning explicit state variables S Nath, V Liu, A Chan, X Li, A White, M White International Conference on Learning Representations (ICLR) 2020, 2019 | 5 | 2019 |
| CAMMARL: Conformal Action Modeling in Multi Agent Reinforcement Learning N Gupta, S Nath, SE Kahou arXiv preprint arXiv:2306.11128, 2023 | 1 | 2023 |
| Discovering Object-Centric Generalized Value Functions From Pixels S Nath, GR Subbaraj, K Khetarpal, SE Kahou International Conference on Machine Learning (ICML) 2023, 2023 | 1 | 2023 |
| A Learning Based Framework for Handling Uncertain Lead Times in Multi-Product Inventory Management H Meisheri, S Nath, M Baranwal, H Khadilkar arXiv preprint arXiv:2203.00885, 2022 | 1 | 2022 |
| Fixed Point Propagation: A New Way To Train Recurrent Neural Networks Using Auxiliary Variables S Nath | 1 | 2019 |
| Spectral Temporal Contrastive Learning S Morin, S Nath, SE Kahou, G Wolf NeurIPS 2023 Workshop: Self-Supervised Learning - Theory and Practice, 2023 | | 2023 |
| Locally Constrained Representations in Reinforcement Learning S Nath, R Arora, SE Kahou NeurIPS 2022: Deep RL Workshop, 2022 | | 2022 |
| Follow your Nose: Using General Value Functions for Directed Exploration in Reinforcement Learning S Nath, O Shelke, D Kalwar, H Meisheri, H Khadilkar International Conference on Autonomous Agents and Multiagent Systems (AAMAS …, 2022 | | 2022 |
| SIBRE: Self Improvement Based REwards for Adaptive Feedback in Reinforcement Learning S Nath, R Verma, A Ray, H Khadilkar The International Conference on Autonomous Agents and Multiagent Systems, 2020 | | 2020 |
| A Fixed-Point Formulation for Recurrent Neural Networks S Nath, T Jafferjee, M White | | 2018 |
| Unsupervised Event Outlier Detection in Continuous Time S Nath, YC Lui, S Liu | | |
Harshad KhadilkarPrincipal Research Scientist, Franklin Templeton; Visiting Associate Professor, IIT BombayVerified email at iitb.ac.in
