Ryan Riegel

According to our database, Ryan Riegel authored at least 15 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A Neuro-Symbolic Approach to Multi-Agent RL for Interpretability and Probabilistic Decision Making.

Chitra Subramanian, Miao Liu, Naweed Khan, Jonathan Lenchner, Aporva Amarnath, Sarathkrishna Swaminathan, Ryan Riegel, Alexander Gray

CoRR, 2024

2023

Approximate Inference in Logical Credal Networks.

Radu Marinescu, Haifeng Qian, Alexander G. Gray, Debarun Bhattacharjya, Francisco Barahona, Tian Gao, Ryan Riegel

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases.

Sumit Neelam, Udit Sharma, Hima Karanam, Shajith Ikbal, Pavan Kapanipathi, Ibrahim Abdelaziz, Nandana Mihindukulasooriya, Young-Suk Lee, Santosh K. Srivastava, Cezar Pendus, Saswati Dana, Dinesh Garg, Achille Fokoue, G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Srinivas Ravishankar, Sairam Gurajada, Maria Chang, Rosario Uceda-Sosa, Salim Roukos, Alexander G. Gray, Guilherme Lima, Ryan Riegel, Francois P. S. Luus, L. Venkata Subramaniam

CoRR, 2022

Logical Credal Networks.

Radu Marinescu, Haifeng Qian, Alexander G. Gray, Debarun Bhattacharjya, Francisco Barahona, Tian Gao, Ryan Riegel, Pravinda Sahu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

SYGMA: A System for Generalizable and Modular Question Answering Over Knowledge Bases.

Sumit Neelam, Udit Sharma, Hima Karanam, Shajith Ikbal, Pavan Kapanipathi, Ibrahim Abdelaziz, Nandana Mihindukulasooriya, Young-Suk Lee, Santosh K. Srivastava, Cezar Pendus, Saswati Dana, Dinesh Garg, Achille Fokoue, G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Srinivas Ravishankar, Sairam Gurajada, Maria Chang, Rosario Uceda-Sosa, Salim Roukos, Alexander Gray, Guilherme Lima, Ryan Riegel, Francois P. S. Luus, L. Venkata Subramaniam

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Neuro-Symbolic Inductive Logic Programming with Logical Neural Networks.

Prithviraj Sen, Breno W. S. R. de Carvalho, Ryan Riegel, Alexander G. Gray

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases.

Sumit Neelam, Udit Sharma, Hima Karanam, Shajith Ikbal, Pavan Kapanipathi, Ibrahim Abdelaziz, Nandana Mihindukulasooriya, Young-Suk Lee, Santosh K. Srivastava, Cezar Pendus, Saswati Dana, Dinesh Garg, Achille Fokoue, G. P. Shrivatsa Bhargav, Dinesh Khandelwal, Srinivas Ravishankar, Sairam Gurajada, Maria Chang, Rosario Uceda-Sosa, Salim Roukos, Alexander G. Gray, Guilherme Lima, Ryan Riegel, Francois P. S. Luus, L. Venkata Subramaniam

CoRR, 2021

Logic Embeddings for Complex Query Answering.

Francois P. S. Luus, Prithviraj Sen, Pavan Kapanipathi, Ryan Riegel, Ndivhuwo Makondo, Thabang Lebese, Alexander G. Gray

CoRR, 2021

Training Logical Neural Networks by Primal-Dual Methods for Neuro-Symbolic Reasoning.

Songtao Lu, Naweed Khan, Ismail Yunus Akhalwaya, Ryan Riegel, Lior Horesh, Alexander G. Gray

Proceedings of the IEEE International Conference on Acoustics, 2021

Leveraging Abstract Meaning Representation for Knowledge Base Question Answering.

Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar, Salim Roukos, Alexander G. Gray, Ramón Fernandez Astudillo, Maria Chang, Cristina Cornelio, Saswati Dana, Achille Fokoue, Dinesh Garg, Alfio Gliozzo, Sairam Gurajada, Hima Karanam, Naweed Khan, Dinesh Khandelwal, Young-Suk Lee, Yunyao Li, Francois P. S. Luus, Ndivhuwo Makondo, Nandana Mihindukulasooriya, Tahira Naseem, Sumit Neelam, Lucian Popa, Revanth Gangi Reddy, Ryan Riegel, Gaetano Rossiello, Udit Sharma, G. P. Shrivatsa Bhargav, Mo Yu

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020

Question Answering over Knowledge Bases by Leveraging Semantic Parsing and Neuro-Symbolic Reasoning.

Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar, Salim Roukos, Alexander G. Gray, Ramón Fernandez Astudillo, Maria Chang, Cristina Cornelio, Saswati Dana, Achille Fokoue, Dinesh Garg, Alfio Gliozzo, Sairam Gurajada, Hima Karanam, Naweed Khan, Dinesh Khandelwal, Young-Suk Lee, Yunyao Li, Francois P. S. Luus, Ndivhuwo Makondo, Nandana Mihindukulasooriya, Tahira Naseem, Sumit Neelam, Lucian Popa, Revanth Gangi Reddy, Ryan Riegel, Gaetano Rossiello, Udit Sharma, G. P. Shrivatsa Bhargav, Mo Yu

CoRR, 2020

Foundations of Reasoning with Uncertainty via Real-valued Logics.

Ronald Fagin, Ryan Riegel, Alexander G. Gray

CoRR, 2020

Logical Neural Networks.

Ryan Riegel, Alexander G. Gray, Francois P. S. Luus, Naweed Khan, Ndivhuwo Makondo, Ismail Yunus Akhalwaya, Haifeng Qian, Ronald Fagin, Francisco Barahona, Udit Sharma, Shajith Ikbal, Hima Karanam, Sumit Neelam, Ankita Likhyani, Santosh K. Srivastava

CoRR, 2020

2014

Generalized N-body problems: a framework for scalable computation.

Ryan Riegel

PhD thesis, 2014

2008

Massive-Scale Kernel Discriminant Analysis: Mining for Quasars.

Ryan Riegel, Alexander G. Gray, Gordon Richards

Proceedings of the SIAM International Conference on Data Mining, 2008