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Publication search results
found 7 matches
- 2024
- Rui Gao, Indu Kant Deo, Rajeev K. Jaiman:
A finite element-inspired hypergraph neural network: Application to fluid dynamics simulations. J. Comput. Phys. 504: 112866 (2024) - Indu Kant Deo, Akash Venkateshwaran, Rajeev K. Jaiman:
Continual Learning of Range-Dependent Transmission Loss for Underwater Acoustic using Conditional Convolutional Neural Net. CoRR abs/2404.08091 (2024) - 2022
- Indu Kant Deo, Rajeev Jaiman:
Learning Wave Propagation with Attention-Based Convolutional Recurrent Autoencoder Net. CoRR abs/2201.06628 (2022) - Indu Kant Deo, Rui Gao, Rajeev Jaiman:
Combined space-time reduced-order model with 3D deep convolution for extrapolating fluid dynamics. CoRR abs/2211.00307 (2022) - Rui Gao, Indu Kant Deo, Rajeev K. Jaiman:
Node-Element Hypergraph Message Passing for Fluid Dynamics Simulations. CoRR abs/2212.14545 (2022) - 2019
- G. Rahul Kranti Kiran, Indu Kant Deo, Sanskar Agrawal, Siddhant Haldar, Het Shah, Sohan Rudra, Harsh Maheshwari, Aditya Rathore, Poojan Shah, Ashwin Nehete, Debashish Chakravarty:
Design and Implementation of Autonomous Ground Vehicle for Constrained Environments. IRC 2019: 236-239 - 2018
- Sanskar Agrawal, Indu Kant Deo, Siddhant Haldar, G. Rahul Kranti Kiran, Vaibhav Lodhi, Debashish Chakravarty:
Off-Road Lane Detection Using Superpixel Clustering and RANSAC Curve Fitting. ICARCV 2018: 1942-1946
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