A review of some techniques for inclusion of domain-knowledge into deep neural networks T Dash, S Chitlangia, A Ahuja, A Srinivasan Scientific Reports 12 (1), 1-15, 2022 | 123 | 2022 |
Widening access to applied machine learning with tinyml VJ Reddi, B Plancher, S Kennedy, L Moroney, P Warden, A Agarwal, ... arXiv preprint arXiv:2106.04008, 2021 | 56 | 2021 |
Investigating the impact of multi-lidar placement on object detection for autonomous driving H Hu, Z Liu, S Chitlangia, A Agnihotri, D Zhao Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 41 | 2022 |
Multilingual spoken words corpus M Mazumder, S Chitlangia, C Banbury, Y Kang, JM Ciro, K Achorn, ... Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021 | 41 | 2021 |
QuaRL: Quantization for Fast and Environmentally Sustainable Reinforcement Learning S Krishnan, M Lam, S Chitlangia, Z Wan, G Barth-maron, A Faust, ... | 41* | |
Reinforcement learning and its connections with neuroscience and psychology A Subramanian, S Chitlangia, V Baths Neural Networks, 2021 | 34 | 2021 |
Incorporating domain knowledge into deep neural networks T Dash, S Chitlangia, A Ahuja, A Srinivasan arXiv preprint arXiv:2103.00180, 2021 | 19 | 2021 |
Self supervised pre-training for large scale tabular data S Chitlangia, A Muralidhar, R Agarwal NeurIPS 2022 First Table Representation Workshop, 2022 | 4 | 2022 |
Real-time detection of robotic traffic in online advertising A Muralidhar, S Chitlangia, R Agarwal, M Ahmed Proceedings of the AAAI Conference on Artificial Intelligence 37 (13), 15551 …, 2023 | 1 | 2023 |
Scaling generative pre-training for user ad activity sequences S Chitlangia, KR Kesari, R Agarwal | 1 | 2023 |
Learning explainable network request signatures for robot detection R Agarwal, S Chitlangia, A Muralidhar, A Niranjan, A Sharma, ... | | 2023 |