| Composition-based Multi-Relational Graph Convolutional Networks S Vashishth, S Sanyal, V Nitin, P Talukdar International Conference on Learning Representations (ICLR), 2020, 2019 | 824 | 2019 |
| 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 32, 1511-1522, 2019 | 386 | 2019 |
| Interacte: Improving convolution-based knowledge graph embeddings by increasing feature interactions S Vashishth, S Sanyal, V Nitin, N Agrawal, P Talukdar Proceedings of the AAAI conference on artificial intelligence 34 (03), 3009-3016, 2020 | 339 | 2020 |
| Multitask Learning Strengthens Adversarial Robustness C Mao, A Gupta, V Nitin, B Ray, S Song, J Yang, C Vondrick Proceedings of the 16th European Conference on Computer Vision (ECCV), 2020, 2020 | 86 | 2020 |
| 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 | 67 | 2020 |
| CARGO: AI-Guided Dependency Analysis for Migrating Monolithic Applications to Microservices Architecture V Nitin, S Asthana, B Ray, R Krishna 37th IEEE/ACM International Conference on Automated Software Engineering, 1-12, 2022 | 9 | 2022 |
| DIRECT: A Transformer-based Model for Decompiled Identifier Renaming V Nitin, A Saieva, B Ray, G Kaiser Proceedings of the 1st Workshop on Natural Language Processing for …, 2021 | 5 | 2021 |
| SGD on Neural Networks learns Robust Features before Non-Robust V Nitin | 2 | 2020 |
| Team AcYut Team Description Paper 2018 V Nitin, A Jain, S Srinivasan, A Bhat, D Pandya, A Ramachandran, ... | 1* | |
| Yuga: Automatically Detecting Lifetime Annotation Bugs in the Rust Language V Nitin, A Mulhern, S Arora, B Ray arXiv preprint arXiv:2310.08507, 2023 | | 2023 |
