| Deep attentive learning for stock movement prediction from social media text and company correlations R Sawhney, S Agarwal, A Wadhwa, RR Shah Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 92 | 2020 |
| Stock selection via spatiotemporal hypergraph attention network: A learning to rank approach R Sawhney, S Agarwal, A Wadhwa, T Derr, RR Shah Proceedings of the AAAI Conference on Artificial Intelligence 35 (1), 497-504, 2021 | 80 | 2021 |
| Spatiotemporal hypergraph convolution network for stock movement forecasting R Sawhney, S Agarwal, A Wadhwa, RR Shah 2020 IEEE International Conference on Data Mining (ICDM), 482-491, 2020 | 56 | 2020 |
| Exploring the scale-free nature of stock markets: Hyperbolic graph learning for algorithmic trading R Sawhney, S Agarwal, A Wadhwa, R Shah Proceedings of the Web Conference 2021, 11-22, 2021 | 31 | 2021 |
| FAST: Financial news and tweet based time aware network for stock trading R Sawhney, A Wadhwa, S Agarwal, R Shah Proceedings of the 16th conference of the european chapter of the …, 2021 | 30 | 2021 |
| Cryptocurrency bubble detection: a new stock market dataset, financial task & hyperbolic models R Sawhney, S Agarwal, V Mittal, P Rosso, V Nanda, S Chava arXiv preprint arXiv:2206.06320, 2022 | 18 | 2022 |
| Quantitative day trading from natural language using reinforcement learning R Sawhney, A Wadhwa, S Agarwal, R Shah Proceedings of the 2021 Conference of the North American Chapter of the …, 2021 | 16 | 2021 |
| Towards suicide ideation detection through online conversational context R Sawhney, S Agarwal, AT Neerkaje, N Aletras, P Nakov, L Flek Proceedings of the 45th international ACM SIGIR conference on research and …, 2022 | 13 | 2022 |
| GPolS: A contextual graph-based language model for analyzing parliamentary debates and political cohesion R Sawhney, A Wadhwa, S Agarwal, R Shah Proceedings of the 28th International Conference on Computational …, 2020 | 12 | 2020 |
| Text-Augmented Open Knowledge Graph Completion via Pre-Trained Language Models P Jiang, S Agarwal, B Jin, X Wang, J Sun, J Han arXiv preprint arXiv:2305.15597, 2023 | 11 | 2023 |
| Hyperbolic online time stream modeling R Sawhney, S Agarwal, M Thakkar, A Wadhwa, RR Shah Proceedings of the 44th International ACM SIGIR conference on research and …, 2021 | 11 | 2021 |
| HYPMIX: Hyperbolic Interpolative Data Augmentation R Sawhney, M Thakkar, S Agarwal, D Jin, D Yang, L Flek Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 11 | 2021 |
| Deep residual neural networks for image in audio steganography (Workshop Paper) S Agarwal, S Venkatraman 2020 IEEE Sixth International Conference on Multimedia Big Data (BigMM), 430-434, 2020 | 11* | 2020 |
| Think: Temporal hypergraph hyperbolic network S Agarwal, R Sawhney, M Thakkar, P Nakov, J Han, T Derr 2022 IEEE International Conference on Data Mining (ICDM), 849-854, 2022 | 6 | 2022 |
| Modeling financial uncertainty with multivariate temporal entropy-based curriculums R Sawhney, A Wadhwa, A Mangal, V Mittal, S Agarwal, RR Shah Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial …, 2021 | 4 | 2021 |
| TEC: A Time Evolving Contextual Graph Model for Speaker State Analysis in Political Debates R Sawhney, S Agarwal, A Wadhwa, R Shah Proceedings of the Thirtieth International Joint Conference on Artificial …, 2021 | 2 | 2021 |
| DynaMiTE: Discovering explosive topic evolutions with user guidance N Balepur, S Agarwal, KV Ramanan, S Yoon, D Yang, J Han Findings of the Association for Computational Linguistics: ACL 2023, 194-217, 2023 | 1 | 2023 |
| Orthogonal Multi-Manifold Enriching of Directed Networks R Sawhney, S Agarwal, AT Neerkaje, KJ Pathak International Conference on Artificial Intelligence and Statistics, 6074-6086, 2022 | 1 | 2022 |
| Hyphen: Hyperbolic hawkes attention for text streams S Agarwal, R Sawhney, S Ahuja, R Soun, S Chava Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 1 | 2022 |
| Improving Retrieval in Theme-specific Applications using a Corpus Topical Taxonomy SK Kang, S Agarwal, B Jin, D Lee, H Yu, J Han arXiv preprint arXiv:2403.04160, 2024 | | 2024 |
Ramit SawhneyTower Research Capital, Georgia TechVerified email at tower-research.com
