Saurabh Mathur

According to our database, Saurabh Mathur authored at least 19 papers between 2019 and 2026.

Collaborative distances:

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

2026

Imitation learning for clinical decision support in pediatric ECMO.

Fateme Golivand Darvishvand, Michael A. Skinner, Saurabh Mathur, Ameet Soni, Phillip Reeder, Kristian Kersting, Lakshmi Raman, Sriraam Natarajan

CoRR, May, 2026

Context-specific Credibility-aware Multimodal Fusion with Conditional Probabilistic Circuits.

Pranuthi Tenali, Sahil Sidheekh, Saurabh Mathur, Erik Blasch, Kristian Kersting, Sriraam Natarajan

CoRR, March, 2026

Recursive Inference Machines for Neural Reasoning.

Mieszko Komisarczyk, Saurabh Mathur, Maurice Kraus, Sriraam Natarajan, Kristian Kersting

CoRR, March, 2026

EHR Sampling Interval Bias Detection and Burden of Blood Pressure Excursions: Implications for Clinical Decision Support and Model Validity in Pediatric ECMO.

Neel Shah, Ethan Sanford, David R. Busch, Ranveer Singh, Saurabh Mathur, Jayesh Sharma, Philip Reeder, Sriraam Natarajan, Lakshmi Raman

Inf., 2026

2025

LLMs for Causal Reasoning in Medicine? A Call for Caution.

Saurabh Mathur, Ranveer Singh, Michael A. Skinner, Predrag Radivojac, David M. Haas, Lakshmi Raman, Sriraam Natarajan

Proceedings of the 13th ACM IKDD International Conference on Data Science, 2025

Representing Multi-Relational Data via Statistical Relational Learning and Graph Convolutional Networks.

Devendra Singh Dhami, Saurabh Mathur, Siwen Yan, Sriraam Natarajan

Proceedings of the 13th ACM IKDD International Conference on Data Science, 2025

Credibility-Aware Multimodal Fusion Using Probabilistic Circuits.

Sahil Sidheekh, Pranuthi Tenali, Saurabh Mathur, Erik Blasch, Kristian Kersting, Sriraam Natarajan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

LLM-Guided Causal Bayesian Network Construction for Pediatric Patients on ECMO.

Saurabh Mathur, Ranveer Singh, Michael A. Skinner, Ethan Sanford, Neel Shah, Phillip Reeder, Lakshmi Raman, Sriraam Natarajan

Proceedings of the Artificial Intelligence in Medicine - 23rd International Conference, 2025

Human-in-the-loop or AI-in-the-loop? Automate or Collaborate?

Sriraam Natarajan, Saurabh Mathur, Sahil Sidheekh, Wolfgang Stammer, Kristian Kersting

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

A Unified Framework for Human-Allied Learning of Probabilistic Circuits.

Athresh Karanam, Saurabh Mathur, Sahil Sidheekh, Sriraam Natarajan

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Credibility-Aware Multi-Modal Fusion Using Probabilistic Circuits.

Sahil Sidheekh, Pranuthi Tenali, Saurabh Mathur, Erik Blasch, Kristian Kersting, Sriraam Natarajan

CoRR, 2024

Knowledge Intensive Learning of Credal Networks.

Saurabh Mathur, Alessandro Antonucci, Sriraam Natarajan

Proceedings of the Uncertainty in Artificial Intelligence, 2024

On the Robustness and Reliability of Late Multi-Modal Fusion using Probabilistic Circuits.

Sahil Sidheekh, Pranuthi Tenali, Saurabh Mathur, Erik Blasch, Sriraam Natarajan

Proceedings of the 27th International Conference on Information Fusion, 2024

Deep Tractable Probabilistic Models.

Sahil Sidheekh, Saurabh Mathur, Athresh Karanam, Sriraam Natarajan

Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD), 2024

Modeling Multiple Adverse Pregnancy Outcomes: Learning from Diverse Data Sources.

Saurabh Mathur, Veerendra P. Gadekar, Rashika Ramola, Peixin Wang, Ramachandran Thiruvengadam, David M. Haas, Shinjini Bhatnagar, Nitya Wadhwa, Garbhini Study Group, Predrag Radivojac, Himanshu Sinha, Kristian Kersting, Sriraam Natarajan

Proceedings of the Artificial Intelligence in Medicine - 22nd International Conference, 2024

2023

Knowledge Intensive Learning of Cutset Networks.

Saurabh Mathur, Vibhav Gogate, Sriraam Natarajan

Proceedings of the Uncertainty in Artificial Intelligence, 2023

2022

Explaining Deep Tractable Probabilistic Models: The sum-product network case.

Athresh Karanam, Saurabh Mathur, Predrag Radivojac, David M. Haas, Kristian Kersting, Sriraam Natarajan

Proceedings of the International Conference on Probabilistic Graphical Models, 2022

2021

Explaining Deep Tractable Probabilistic Models: The sum-product network case.

Athresh Karanam, Saurabh Mathur, Predrag Radivojac, Kristian Kersting, Sriraam Natarajan

CoRR, 2021

2019

A scaled-down neural conversational model for chatbots.

Saurabh Mathur, Daphne Lopez

Concurr. Comput. Pract. Exp., 2019