| Hypergcn: A new method for training graph convolutional networks on hypergraphs N Yadati, M Nimishakavi, P Yadav, V Nitin, A Louis, P Talukdar Advances in Neural Information Processing Systems, 1511-1522, 2019 | 463 | 2019 |
| Kvqa: Knowledge-aware visual question answering S Shah, A Mishra, N Yadati, PP Talukdar Proceedings of the AAAI conference on artificial intelligence 33 (01), 8876-8884, 2019 | 189 | 2019 |
| Nhp: Neural hypergraph link prediction N Yadati, V Nitin, M Nimishakavi, P Yadav, A Louis, P Talukdar Proceedings of the 29th ACM international conference on information …, 2020 | 93* | 2020 |
| Mt-cgcnn: Integrating crystal graph convolutional neural network with multitask learning for material property prediction S Sanyal, J Balachandran, N Yadati, A Kumar, P Rajagopalan, S Sanyal, ... arXiv preprint arXiv:1811.05660, 2018 | 53 | 2018 |
| Neural message passing for multi-relational ordered and recursive hypergraphs N Yadati Advances in Neural Information Processing Systems 33, 3275-3289, 2020 | 40 | 2020 |
| Graph-based deep learning in natural language processing S Vashishth, N Yadati, P Talukdar Proceedings of the 7th ACM IKDD CoDS and 25th COMAD, 371-372, 2020 | 25 | 2020 |
| Lovasz convolutional networks P Yadav, M Nimishakavi, N Yadati, S Vashishth, A Rajkumar, P Talukdar The 22nd international conference on artificial intelligence and statistics …, 2019 | 15 | 2019 |
| Knowledge base question answering through recursive hypergraphs N Yadati, RS Dayanidhi, S Vaishnavi, KM Indira, G Srinidhi Proceedings of the 16th conference of the European chapter of the …, 2021 | 14 | 2021 |
| Biologically Plausible Neural Networks via Evolutionary Dynamics and Dopaminergic Plasticity S Gorantla, A Louis, CH Papadimitriou, S Vempala, N Yadati | 4 | 2019 |
| Graph neural networks for soft semi-supervised learning on hypergraphs N Yadati, T Gao, S Asoodeh, P Talukdar, A Louis Pacific-Asia Conference on Knowledge Discovery and Data Mining, 447-458, 2021 | 3 | 2021 |
| HyperGCN: Hypergraph convolutional networks for semi-supervised learning and combinatorial optimisation N Yadati, M Nimishakavi, P Yadav, V Nitin, A Louis, P Talukdar arXiv preprint arXiv:1809.02589, 2019 | 3 | 2019 |
| A convex formulation for graph convolutional training: Two layer case N Yadati 2022 IEEE International Conference on Data Mining (ICDM), 1281-1286, 2022 | 2 | 2022 |
| HEAL: Unlocking the Potential of Learning on Hypergraphs Enriched with Attributes and Layers N Yadati, T Kumar, D Maurya, B Ravindran, P Talukdar Learning on Graphs Conference, 34: 1-34: 25, 2024 | | 2024 |
| GAINER: Graph Machine Learning with Node-specific Radius for Classification of Short Texts and Documents N Yadati Proceedings of the 18th Conference of the European Chapter of the …, 2024 | | 2024 |
| Deep Learning over Hypergraphs N Yadati | | 2021 |
| Hypergcn: A new method for training graph convolutional networks on hypergraphs N Yadati, M Nimishakavi, P Yadav, V Nitin, A Louis, P Talukdar Advances in Neural Information Processing Systems, 1511-1522, 2019 | | 2019 |
