Vaidyanathan P. R.
Address:
Vaidyanathan P. R.
Technische Universität Wien
Institute of Logic and Computation
Favoritenstraße 9–11, E192-01
1040 Wien
Austria
| Room: | HA0406 |
| Phone: | +43(1)58801–192139 |
| Email: | vaidyanathan@ac.tuwien.ac.at |
| Web: | http://www.ac.tuwien.ac.at/people/vaidyanathan/ |
orcid.org/0000-0002-3101-2085Publications
11 results| 2026 | |
| [11] | LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Proceedings of the 20th Conference on Neurosymbolic Learning and Reasoning (NeSy 2026), 2026. Note: To appear; preprint: CoRR abs/2608.13333, https://arxiv.org/abs/2608.13333 |
| 2025 | |
| [10] | Generating Streamlining Constraints with Large Language Models Journal of Artificial Intelligence Research, volume 84, pages 16:1–16:19, 2025. Note: Abstract reprint in AAAI 2026, page 39900 |
| [9] | StreamLLM: Enhancing Constraint Programming with Large Language Model-Generated Streamliners 2025 IEEE/ACM 1st International Workshop on Neuro-Symbolic Software Engineering (NSE), pages 17-22, 5 2025, IEEE Computer Soc.. |
| [8] | Balancing Latin Rectangles with LLM-Generated Streamliners 31st International Conference on Principles and Practice of Constraint Programming, CP 2025, August 10-15, 2025, Glasgow, Scotland (Maria Garcia de la Banda, ed.), volume 340 of LIPIcs, pages 36:1–36:17, 2025, Schloss Dagstuhl - Leibniz-Zentrum für Informatik. |
| [7] | Uncovering and Verifying Optimal Community Structure in Complex Networks: A MaxSAT Approach Computational Science - ICCS 2025 - 25th International Conference, Singapore, July 7-9, 2025, Proceedings, Part II (Michael H. Lees, Wentong Cai, Siew Ann Cheong, Yi Su, David Abramson, Jack J. Dongarra, Peter M. A. Sloot, eds.), volume 15904 of Lecture Notes in Computer Science, pages 35–49, 2025, Springer Verlag. |
| 2024 | |
| [6] | The Power of Collaboration: Learning Large Bayesian Networks at Scale 2024 IEEE 36th International Conference on Tools with Artificial Intelligence (ICTAI), pages 371-378, 2024. |
| 2023 | |
| [5] | Proven optimally-balanced Latin rectangles with SAT Proceedings of CP 2023, the 29th International Conference on Principles and Practice of Constraint Programming (Roland Yap, ed.), volume 280 of LIPIcs, pages 48:1–48:10, 2023, Schloss Dagstuhl - Leibniz-Zentrum für Informatik. |
| 2022 | |
| [4] | Learning Large Bayesian Networks with Expert Constraints 38th Conference on Uncertainty in Artificial Intelligence (UAI 2022), Eindhoven, Netherlands, August 1–5, 2022 (James Cussens, Kun Zhang, eds.), pages 180:1592–1601, 2022. |
| 2021 | |
| [3] | Learning fast-inference Bayesian networks Proceedings of NeurIPS 2021, the Thirty-fifth Conference on Neural Information Processing Systems (M. Ranzato, A. Beygelzimer, K. Nguyen, P.S. Liang, J.W. Vaughan, Y. Dauphin, eds.), pages 17852–17863, 2021. |
| [2] | Turbocharging Treewidth-Bounded Bayesian Network Structure Learning Proceeding of AAAI-21, the Thirty-Fifth AAAI Conference on Artificial Intelligence, pages 3895–3903, 2021, AAAI Press. |
| 2020 | |
| [1] | MaxSAT-Based Postprocessing for Treedepth Proceedings of CP 2020, the 26th International Conference on Principles and Practice of Constraint Programming (Helmut Simonis, ed.), volume 12333 of Lecture Notes in Computer Science, pages 478–495, 2020, Springer Verlag. |
