| Hetegcn: heterogeneous graph convolutional networks for text classification R Ragesh, S Sellamanickam, A Iyer, R Bairi, V Lingam Proceedings of the 14th ACM international conference on web search and data …, 2021 | 91 | 2021 |
| Deep learning for conflicting statements detection in text V Lingam, S Bhuria, M Nair, D Gurpreetsingh, A Goyal, A Sureka PeerJ Preprints, 2018 | 19 | 2018 |
| ALT: towards automating driver license testing using smartphones AU Nambi, I Mehta, A Ghosh, V Lingam, VN Padmanabhan Proceedings of the 17th Conference on Embedded Networked Sensor Systems, 29-42, 2019 | 14 | 2019 |
| Probing graph representations MS Akhondzadeh, V Lingam, A Bojchevski International Conference on Artificial Intelligence and Statistics, 11630-11649, 2023 | 11 | 2023 |
| Simple truncated svd based model for node classification on heterophilic graphs V Lingam, R Ragesh, A Iyer, S Sellamanickam KDD 2021 Workshop on Deep Learning on Graphs: Method and Applications, 2021 | 9 | 2021 |
| A piece-wise polynomial filtering approach for graph neural networks V Lingam, M Sharma, C Ekbote, R Ragesh, A Iyer, S Sellamanickam Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 7 | 2022 |
| User embedding based neighborhood aggregation method for inductive recommendation R Ragesh, S Sellamanickam, V Lingam, A Iyer, R Bairi arXiv preprint arXiv:2102.07575, 2021 | 6 | 2021 |
| A graph convolutional network composition framework for semi-supervised classification R Ragesh, S Sellamanickam, V Lingam, A Iyer arXiv preprint arXiv:2004.03994, 2020 | 5 | 2020 |
| Pitfalls in Evaluating GNNs under Label Poisoning Attacks V Lingam, MS Akhondzadeh, A Bojchevski ICLR 2023 Workshop on Pitfalls of limited data and computation for …, 2023 | 2 | 2023 |
| SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors V Lingam, A Tejaswi, A Vavre, A Shetty, GK Gudur, J Ghosh, A Dimakis, ... ICML 2024 2nd Workshop on Advancing Neural Network Training: Computational …, 2024 | 1 | 2024 |
| Rethinking Label Poisoning for GNNs: Pitfalls and Attacks V Lingam, MS Akhondzadeh, A Bojchevski The Twelfth International Conference on Learning Representations, 2024 | 1 | 2024 |
| GLAM: Graph Learning by Modeling Affinity to Labeled Nodes for Graph Neural Networks V Lingam, A Iyer, R Ragesh ICLR 2021 Workshop on Geometrical and Topological Representation Learning, 2021 | 1 | 2021 |
| Effective Eigendecomposition based Graph Adaptation for Heterophilic Networks V Lingam, R Ragesh, A Iyer, S Sellamanickam arXiv preprint arXiv:2107.13312, 2021 | | 2021 |
| Smartphone-based driver license testing: demo abstract A Ghosh, V Lingam, I Mehta, AU Nambi, VN Padmanabhan, ... Proceedings of the 17th Conference on Embedded Networked Sensor Systems, 400-401, 2019 | | 2019 |
| Effective Polynomial Filter Adaptation for Graph Neural Networks V Lingam, CA Ekbote, M Sharma, R Ragesh, A Iyer, S SELLAMANICKAM | | |
Ramakrishna BairiMicrosoft Research IndiaVerified email at microsoft.com
