Sriraam Natarajan
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
97
Venues
21
Active years
2005–2026
Best venue rank
A*
Where they publish
Papers
97 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | Tractable Sharpness-Aware Learning of Probabilistic Circuits. | Hrithik Suresh, Sahil Sidheekh, Vishnu Shreeram M. P, Sriraam Natarajan, Narayanan Chatapuram Krishnan |
| 2026 | AIME | 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 |
| 2026 | AIME | Causal Models with Tiny Data: The Case of Rural People Living with Dementia. | Ranveer Singh, Saurabh Mathur, Kavimayil P. Komarasamy, Ameet Soni, Cliff Whetung, Wayne Warry, Kristen Jacklin, Melissa Blind, Sriraam Natarajan |
| 2025 | AAAI | A Unified Framework for Human-Allied Learning of Probabilistic Circuits. | Athresh Karanam, Saurabh Mathur, Sahil Sidheekh, Sriraam Natarajan |
| 2025 | AAAI | Human-in-the-loop or AI-in-the-loop? Automate or Collaborate? | Sriraam Natarajan, Saurabh Mathur, Sahil Sidheekh, Wolfgang Stammer, Kristian Kersting |
| 2025 | AIES | IndiCASA: A Dataset and Bias Evaluation Framework for LLMs Using Contrastive Embedding Similarity in the Indian Context. | Santhosh G. S, Akshay Govind S, Gokul S. Krishnan, Balaraman Ravindran, Sriraam Natarajan |
| 2025 | AIME | 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 |
| 2025 | AISTATS | Credibility-Aware Multimodal Fusion Using Probabilistic Circuits. | Sahil Sidheekh, Pranuthi Tenali, Saurabh Mathur, Erik Blasch, Kristian Kersting, Sriraam Natarajan |
| 2025 | PAKDD | Scalable Knowledge Graph Construction from Unstructured Text: A Case Study on Artisanal and Small-Scale Gold Mining. | Debashis Gupta, Aditi Golder, Sahil Sidheekh, Sakib Imtiaz, Sarra Alaqahtani, Fan Yang, Gregory D. Larsen, Miles R. Silman, Luis E. Fernandez, Robert J. Plemmons, Sriraam Natarajan, V. Paul Pauca |
| 2024 | AAAI | Promoting Research Collaboration with Open Data Driven Team Recommendation in Response to Call for Proposals. | Siva Likitha Valluru, Biplav Srivastava, Sai Teja Paladi, Siwen Yan, Sriraam Natarajan |
| 2024 | AIME | 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 |
| 2024 | COMAD | Deep Tractable Probabilistic Models. | Sahil Sidheekh, Saurabh Mathur, Athresh Karanam, Sriraam Natarajan |
| 2024 | FUSION | On the Robustness and Reliability of Late Multi-Modal Fusion using Probabilistic Circuits. | Sahil Sidheekh, Pranuthi Tenali, Saurabh Mathur, Erik Blasch, Sriraam Natarajan |
| 2024 | IJCAI | Building Expressive and Tractable Probabilistic Generative Models: A Review. | Sahil Sidheekh, Sriraam Natarajan |
| 2024 | UAI | Knowledge Intensive Learning of Credal Networks. | Saurabh Mathur, Alessandro Antonucci, Sriraam Natarajan |
| 2024 | SACMAT | Utilizing Threat Partitioning for More Practical Network Anomaly Detection. | Brian Ricks, Patrick Tague, Bhavani Thuraisingham, Sriraam Natarajan |
| 2023 | AAAI | Never Ending Reasoning and Learning: Opportunities and Challenges. | Sriraam Natarajan, Kristian Kersting |
| 2023 | COMAD | Active Feature Acquisition via Human Interaction in Relational domains. | Nandini Ramanan, Phillip Odom, Kristian Kersting, Sriraam Natarajan |
| 2023 | UAI | Knowledge Intensive Learning of Cutset Networks. | Saurabh Mathur, Vibhav Gogate, Sriraam Natarajan |
| 2023 | UAI | Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference. | Sahil Sidheekh, Kristian Kersting, Sriraam Natarajan |
| 2022 | AIME | An Anytime Querying Algorithm for Predicting Cardiac Arrest in Children: Work-in-Progress. | Michael A. Skinner, Priscilla Yu, Lakshmi Raman, Sriraam Natarajan |
| 2022 | AISTATS | Relational Neural Markov Random Fields. | Yuqiao Chen, Sriraam Natarajan, Nicholas Ruozzi |
| 2022 | FUSION | Hybrid Deep RePReL: Integrating Relational Planning and Reinforcement Learning for Information Fusion. | Harsha Kokel, Nikhilesh Prabhakar, Balaraman Ravindran, Erik Blasch, Prasad Tadepalli, Sriraam Natarajan |
| 2021 | AAAI | Relational Boosted Bandits. | Ashutosh Kakadiya, Sriraam Natarajan, Balaraman Ravindran |
| 2021 | AIME | Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. | Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan |
| 2021 | AIME | A Probabilistic Approach to Extract Qualitative Knowledge for Early Prediction of Gestational Diabetes. | Athresh Karanam, Alexander L. Hayes, Harsha Kokel, David M. Haas, Predrag Radivojac, Sriraam Natarajan |
| 2021 | COMAD | Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning. | Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan |
| 2021 | COMAD | A Clustering based Selection Framework for Cost Aware and Test-time Feature Elicitation. | Srijita Das, Rishabh K. Iyer, Sriraam Natarajan |
| 2021 | ILP | Non-parametric Learning of Embeddings for Relational Data Using Gaifman Locality Theorem. | Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, Sriraam Natarajan |
| 2021 | KR | Beyond Simple Images: Human Knowledge-Guided GANs for Clinical Data Generation. | Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan |
| 2020 | AAAI | A Unified Framework for Knowledge Intensive Gradient Boosting: Leveraging Human Experts for Noisy Sparse Domains. | Harsha Kokel, Phillip Odom, Shuo Yang, Sriraam Natarajan |
| 2020 | IJCAI | Lifted Hybrid Variational Inference. | Yuqiao Chen, Yibo Yang, Sriraam Natarajan, Nicholas Ruozzi |
| 2020 | KDD | Cost Aware Feature Elicitation. | Srijita Das, Rishabh K. Iyer, Sriraam Natarajan |
| 2020 | KDD | Knowledge Intensive Learning of Generative Adversarial Networks. | Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan |
| 2019 | AAAI | Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs. | Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting, Sriraam Natarajan |
| 2019 | IJCAI | Lifted Message Passing for Hybrid Probabilistic Inference. | Yuqiao Chen, Nicholas Ruozzi, Sriraam Natarajan |
| 2019 | ILP | Neural Networks for Relational Data. | Navdeep Kaur, Gautam Kunapuli, Saket Joshi, Kristian Kersting, Sriraam Natarajan |
| 2018 | AAAI | Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains. | Alejandro Molina, Antonio Vergari, Nicola Di Mauro, Sriraam Natarajan, Floriana Esposito, Kristian Kersting |
| 2018 | FUSION | Control Diffusion of Information Collection for Situation Understanding Using Boosting MLNs. | Erik Blasch, Robert Cruise, Sriraam Natarajan, Ali K. Raz, Tim Kelly |
| 2018 | IJCAI | On Whom Should I Perform this Lab Test Next? An Active Feature Elicitation Approach. | Sriraam Natarajan, Srijita Das, Nandini Ramanan, Gautam Kunapuli, Predrag Radivojac |
| 2018 | KR | Structure Learning for Relational Logistic Regression: An Ensemble Approach. | Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan |
| 2017 | AAAI | Active Preference Elicitation for Planning. | Mayukh Das, Md. Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan |
| 2017 | AAAI | Knowledge-Based Morphological Classification of Galaxies from Vision Features. | Devendra Singh Dhami, David Leake, Sriraam Natarajan |
| 2017 | AAAI | Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions. | Alejandro Molina, Sriraam Natarajan, Kristian Kersting |
| 2017 | ACL | Towards Problem Solving Agents that Communicate and Learn. | Anjali Narayan-Chen, Colin Graber, Mayukh Das, Md. Rakibul Islam, Soham Dan, Sriraam Natarajan, Janardhan Rao Doppa, Julia Hockenmaier, Martha Palmer, Dan Roth |
| 2017 | AIME | Identifying Parkinson's Patients: A Functional Gradient Boosting Approach. | Devendra Singh Dhami, Ameet Soni, David Page, Sriraam Natarajan |
| 2017 | CHASE | Does Race Play a Role in Invasive Procedure Treatments? An Initial Analysis. | Noah Hammarlund, Sriraam Natarajan |
| 2017 | CHASE | Boosting for Postpartum Depression Prediction. | Sriraam Natarajan, Annu Prabhakar, Nandini Ramanan, Anna N. Baglione, Katie A. Siek, Kay Connelly |
| 2017 | ILP | Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach. | Navdeep Kaur, Gautam Kunapuli, Tushar Khot, Kristian Kersting, William Cohen, Sriraam Natarajan |
| 2016 | AAAI | Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach. | Shuo Yang, Tushar Khot, Kristian Kersting, Sriraam Natarajan |
| 2016 | CHASE | Identifying Rare Diseases from Behavioural Data: A Machine Learning Approach. | Haley MacLeod, Shuo Yang, Kim Oakes, Kay Connelly, Sriraam Natarajan |
| 2016 | ILP | Inductive Logic Programming Meets Relational Databases: Efficient Learning of Markov Logic Networks. | Marcin Malec, Tushar Khot, James G. Nagy, Erik Blask, Sriraam Natarajan |
| 2016 | ILP | Learning Through Advice-Seeking via Transfer. | Phillip Odom, Raksha Kumaraswamy, Kristian Kersting, Sriraam Natarajan |
| 2016 | ILP | Learning Relational Dependency Networks for Relation Extraction. | Ameet Soni, Dileep Viswanathan, Jude W. Shavlik, Sriraam Natarajan |
| 2016 | SDM | Scaling Lifted Probabilistic Inference and Learning Via Graph Databases. | Mayukh Das, Yuqing Wu, Tushar Khot, Kristian Kersting, Sriraam Natarajan |
| 2015 | AAAI | Knowledge-Based Probabilistic Logic Learning. | Phillip Odom, Tushar Khot, Reid B. Porter, Sriraam Natarajan |
| 2015 | AAAI | Active Advice Seeking for Inverse Reinforcement Learning. | Phillip Odom, Sriraam Natarajan |
| 2015 | AAAI | Learning to Reject Sequential Importance Steps for Continuous-Time Bayesian Networks. | Jeremy C. Weiss, Sriraam Natarajan, C. David Page Jr. |
| 2015 | AIME | Extracting Adverse Drug Events from Text Using Human Advice. | Phillip Odom, Vishal Bangera, Tushar Khot, David Page, Sriraam Natarajan |
| 2015 | AIME | Modeling Coronary Artery Calcification Levels from Behavioral Data in a Clinical Study. | Shuo Yang, Kristian Kersting, Greg Terry, Jeffrey Carr, Sriraam Natarajan |
| 2015 | FlAIRS | Anomaly Detection in Text: The Value of Domain Knowledge. | Raksha Kumaraswamy, Anurag Wazalwar, Tushar Khot, Jude W. Shavlik, Sriraam Natarajan |
| 2015 | ICDM | Transfer Learning via Relational Type Matching. | Raksha Kumaraswamy, Phillip Odom, Kristian Kersting, David Leake, Sriraam Natarajan |
| 2014 | AAAI | Preface. | Guy Van den Broeck, Kristian Kersting, Sriraam Natarajan, David Poole |
| 2014 | AAAI | Relational Logistic Regression: The Directed Analog of Markov Logic Networks. | Seyed Mehran Kazemi, David Buchman, Kristian Kersting, Sriraam Natarajan, David Poole |
| 2014 | AAAI | Relational One-Class Classification: A Non-Parametric Approach. | Tushar Khot, Sriraam Natarajan, Jude W. Shavlik |
| 2014 | AAAI | Classification from One Class of Examples for Relational Domains. | Tushar Khot, Sriraam Natarajan, Jude W. Shavlik |
| 2014 | AAAI | Organizers. | Sriraam Natarajan |
| 2014 | AAAI | A Deeper Empirical Analysis of CBP Algorithm: Grounding Is the Bottleneck. | Shrutika Poyrekar, Sriraam Natarajan, Kristian Kersting |
| 2014 | ICDM | Learning from Imbalanced Data in Relational Domains: A Soft Margin Approach. | Shuo Yang, Tushar Khot, Kristian Kersting, Gautam Kunapuli, Kris Hauser, Sriraam Natarajan |
| 2014 | ILP | Effectively Creating Weakly Labeled Training Examples via Approximate Domain Knowledge. | Sriraam Natarajan, Jose Picado, Tushar Khot, Kristian Kersting, Christopher R, Jude W. Shavlik |
| 2014 | ILP | Statistical Relational Learning for Handwriting Recognition. | Arti Shivram, Tushar Khot, Sriraam Natarajan, Venu Govindaraju |
| 2014 | KR | Relational Logistic Regression. | Seyed Mehran Kazemi, David Buchman, Kristian Kersting, Sriraam Natarajan, David Poole |
| 2014 | SDM | A graphical model approach to ATLAS-free mining of MRI images. | Chris S. Magnano, Ameet Soni, Sriraam Natarajan, Gautam Kunapuli |
| 2013 | AAAI | MapReduce Lifting for Belief Propagation. | Babak Ahmadi, Kristian Kersting, Sriraam Natarajan |
| 2013 | AAAI | Preface. | Vibhav Gogate, Kristian Kersting, Sriraam Natarajan, David Poole |
| 2013 | AAAI | Using Commonsense Knowledge to Automatically Create (Noisy) Training Examples from Text. | Sriraam Natarajan, Jose Picado, Tushar Khot, Kristian Kersting, Christopher R, Jude W. Shavlik |
| 2013 | AAAI | Learning When to Reject an Importance Sample. | Jeremy C. Weiss, Sriraam Natarajan, C. David Page Jr. |
| 2013 | IAAI | Early Prediction of Coronary Artery Calcification Levels Using Machine Learning. | Sriraam Natarajan, Kristian Kersting, Edward Hak-Sing Ip, David R. Jacobs Jr., Jeffrey Carr |
| 2013 | ICDM | Guiding Autonomous Agents to Better Behaviors through Human Advice. | Gautam Kunapuli, Phillip Odom, Jude W. Shavlik, Sriraam Natarajan |
| 2013 | ILP | Accelerating Imitation Learning in Relational Domains via Transfer by Initialization. | Sriraam Natarajan, Phillip Odom, Saket Joshi, Tushar Khot, Kristian Kersting, Prasad Tadepalli |
| 2012 | AAAI | Identifying Adverse Drug Events by Relational Learning. | David Page, Vtor Santos Costa, Sriraam Natarajan, Aubrey Barnard, Peggy L. Peissig, Michael Caldwell |
| 2012 | IAAI | Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records. | Jeremy C. Weiss, Sriraam Natarajan, Peggy L. Peissig, Catherine A. McCarty, David Page |
| 2012 | ICMLA | A Machine Learning Pipeline for Three-Way Classification of Alzheimer Patients from Structural Magnetic Resonance Images of the Brain. | Sriraam Natarajan, Saket Joshi, Baidya Nath Saha, Adam Edwards, Tushar Khot, Elizabeth Moody, Kristian Kersting, Christopher T. Whitlow, Joseph A. Maldjian |
| 2012 | ICMLA | A Novel Hierarchical Level Set with AR-boost for White Matter Lesion Segmentation in Diabetes. | Baidya Nath Saha, Sriraam Natarajan, Gopi Kota, Christopher T. Whitlow, Donald W. Bowden, Jasmin Divers, Barry I. Freedman, Joseph A. Maldjian |
| 2011 | ICDM | Learning Markov Logic Networks via Functional Gradient Boosting. | Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik |
| 2011 | IJCAI | Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach. | Sriraam Natarajan, Saket Joshi, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik |
| 2010 | AAAI | Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models. | Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik |
| 2010 | ICMLA | Multi-Agent Inverse Reinforcement Learning. | Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik |
| 2010 | ILP | Automating the ILP Setup Task: Converting User Advice about Specific Examples into General Background Knowledge. | Trevor Walker, Ciaran O'Reilly, Gautam Kunapuli, Sriraam Natarajan, Richard Maclin, David Page, Jude W. Shavlik |
| 2009 | ICMLA | Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule. | Sriraam Natarajan, Prasad Tadepalli, Gautam Kunapuli, Jude W. Shavlik |
| 2009 | IJCAI | Speeding Up Inference in Markov Logic Networks by Preprocessing to Reduce the Size of the Resulting Grounded Network. | Jude W. Shavlik, Sriraam Natarajan |
| 2009 | UAI | Counting Belief Propagation. | Kristian Kersting, Babak Ahmadi, Sriraam Natarajan |
| 2008 | ILP | Logical Hierarchical Hidden Markov Models for Modeling User Activities. | Sriraam Natarajan, Hung Hai Bui, Prasad Tadepalli, Kristian Kersting, Weng-Keen Wong |
| 2007 | IJCAI | A Decision-Theoretic Model of Assistance. | Alan Fern, Sriraam Natarajan, Kshitij Judah, Prasad Tadepalli |
| 2007 | ILP | A Relational Hierarchical Model for Decision-Theoretic Assistance. | Sriraam Natarajan, Prasad Tadepalli, Alan Fern |
| 2005 | ICML | Dynamic preferences in multi-criteria reinforcement learning. | Sriraam Natarajan, Prasad Tadepalli |
| 2005 | ICML | Learning first-order probabilistic models with combining rules. | Sriraam Natarajan, Prasad Tadepalli, Eric Altendorf, Thomas G. Dietterich, Alan Fern, Angelo C. Restificar |