Sriraam Natarajan

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 104

Top Venues

Publications

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
Modeling Multiple Adverse Pregnancy Outcomes: Learning from Diverse Data Sources. AIME (1) (2024)
Siva Likitha Valluru, Biplav Srivastava, Sai Teja Paladi, Siwen Yan, Sriraam Natarajan
Promoting Research Collaboration with Open Data Driven Team Recommendation in Response to Call for Proposals. AAAI (2024)
Brian Ricks, Patrick Tague, Bhavani Thuraisingham, Sriraam Natarajan
Utilizing Threat Partitioning for More Practical Network Anomaly Detection. SACMAT (2024)
Sahil Sidheekh, Saurabh Mathur, Athresh Karanam, Sriraam Natarajan
Deep Tractable Probabilistic Models. COMAD/CODS (2024)
Siwen Yan, Sriraam Natarajan, Saket Joshi, Roni Khardon, Prasad Tadepalli
Explainable models via compression of tree ensembles. Mach. Learn. 113 (3) (2024)
Sahil Sidheekh, Sriraam Natarajan
Building Expressive and Tractable Probabilistic Generative Models: A Review. CoRR (2024)
Sahil Sidheekh, Pranuthi Tenali, Saurabh Mathur, Erik Blasch, Kristian Kersting, Sriraam Natarajan
Credibility-Aware Multi-Modal Fusion Using Probabilistic Circuits. CoRR (2024)
Athresh Karanam, Saurabh Mathur, Sahil Sidheekh, Sriraam Natarajan
A Unified Framework for Human-Allied Learning of Probabilistic Circuits. CoRR (2024)
Sriraam Natarajan, Kristian Kersting
Never Ending Reasoning and Learning: Opportunities and Challenges. AAAI Bridge Program (2023)
Harsha Kokel, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli
RePReL: a unified framework for integrating relational planning and reinforcement learning for effective abstraction in discrete and continuous domains. Neural Comput. Appl. 35 (23) (2023)
Srijita Das, Nandini Ramanan, Gautam Kunapuli, Predrag Radivojac, Sriraam Natarajan
Active feature elicitation: An unified framework. Frontiers Artif. Intell. 6 (2023)
Alakh Aggarwal, Rishita Bansal, Parth Padalkar, Sriraam Natarajan
MACOptions: Multi-Agent Learning with Centralized Controller and Options Framework. CoRR (2023)
Siwen Yan, Phillip Odom, Sriraam Natarajan
Knowledge-based Refinement of Scientific Publication Knowledge Graphs. CoRR (2023)
Nandini Ramanan, Phillip Odom, Kristian Kersting, Sriraam Natarajan
Active Feature Acquisition via Human Interaction in Relational domains. COMAD/CODS (2023)
Siwen Yan, Phillip Odom, Rahul Pasunuri, Kristian Kersting, Sriraam Natarajan
Learning with privileged and sensitive information: a gradient-boosting approach. Frontiers Artif. Intell. 6 (2023)
Saurabh Mathur, Vibhav Gogate, Sriraam Natarajan
Knowledge Intensive Learning of Cutset Networks. UAI (2023)
Siva Likitha Valluru, Biplav Srivastava, Sai Teja Paladi, Siwen Yan, Sriraam Natarajan
Promoting Research Collaboration with Open Data Driven Team Recommendation in Response to Call for Proposals. CoRR (2023)
Sahil Sidheekh, Kristian Kersting, Sriraam Natarajan
Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference. UAI (2023)
Nandini Ramanan, Phillip Odom, Erik Blasch, Kristian Kersting, Sriraam Natarajan
Relational Active Feature Elicitation for DDDAS. DDDAS (2022)
Yuqiao Chen, Sriraam Natarajan, Nicholas Ruozzi
Relational Neural Markov Random Fields. AISTATS (2022)
Harsha Kokel, Nikhilesh Prabhakar, Balaraman Ravindran, Erik Blasch, Prasad Tadepalli, Sriraam Natarajan
Hybrid Deep RePReL: Integrating Relational Planning and Reinforcement Learning for Information Fusion. FUSION (2022)
Siwen Yan, Sriraam Natarajan, Saket Joshi, Roni Khardon, Prasad Tadepalli
Explainable Models via Compression of Tree Ensembles. CoRR (2022)
Athresh Karanam, Saurabh Mathur, Predrag Radivojac, David M. Haas, Kristian Kersting, Sriraam Natarajan
Explaining Deep Tractable Probabilistic Models: The sum-product network case. PGM (2022)
Michael A. Skinner, Priscilla Yu, Lakshmi Raman, Sriraam Natarajan
An Anytime Querying Algorithm for Predicting Cardiac Arrest in Children: Work-in-Progress. AIME (2022)
Harsha Kokel, Mayukh Das, Md Rakibul Islam, Julia Bonn, Jon Cai, Soham Dan, Anjali Narayan-Chen, Prashant Jayannavar, Janardhan Rao Doppa, Julia Hockenmaier, Sriraam Natarajan, Martha Palmer, Dan Roth
Human-guided Collaborative Problem Solving: A Natural Language based Framework. CoRR (2022)
Athresh Karanam, Saurabh Mathur, Predrag Radivojac, Kristian Kersting, Sriraam Natarajan
Explaining Deep Tractable Probabilistic Models: The sum-product network case. CoRR (2021)
Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan
Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. AIME (2021)
Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahareh Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan
Structure learning for relational logistic regression: an ensemble approach. Data Min. Knowl. Discov. 35 (5) (2021)
Ashutosh Kakadiya, Sriraam Natarajan, Balaraman Ravindran
Relational Boosted Bandits. AAAI (2021)
Athresh Karanam, Alexander L. Hayes, Harsha Kokel, David M. Haas, Predrag Radivojac, Sriraam Natarajan
A Probabilistic Approach to Extract Qualitative Knowledge for Early Prediction of Gestational Diabetes. AIME (2021)
Yuqiao Chen, Sriraam Natarajan, Nicholas Ruozzi
Relational Neural Markov Random Fields. CoRR (2021)
Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli
RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction. ICAPS (2021)
Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan
Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning. COMAD/CODS (2021)
Devendra Singh Dhami, Siwen Yan, Sriraam Natarajan
Bridging Graph Neural Networks and Statistical Relational Learning: Relational One-Class GCN. CoRR (2021)
Matej Zecevic, Devendra Singh Dhami, Athresh Karanam, Sriraam Natarajan, Kristian Kersting
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models. NeurIPS (2021)
Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan
Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach. CoRR (2021)
Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli
Dynamic probabilistic logic models for effective abstractions in RL. CoRR (2021)
Matej Zecevic, Devendra Singh Dhami, Athresh Karanam, Sriraam Natarajan, Kristian Kersting
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models. CoRR (2021)
Srijita Das, Rishabh K. Iyer, Sriraam Natarajan
A Clustering based Selection Framework for Cost Aware and Test-time Feature Elicitation. COMAD/CODS (2021)
Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, Sriraam Natarajan
Non-parametric Learning of Embeddings for Relational Data Using Gaifman Locality Theorem. ILP (2021)
Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan
Beyond Simple Images: Human Knowledge-Guided GANs for Clinical Data Generation. KR (2021)
Navdeep Kaur, Gautam Kunapuli, Sriraam Natarajan
Non-parametric learning of lifted Restricted Boltzmann Machines. Int. J. Approx. Reason. 120 (2020)
Navdeep Kaur, Gautam Kunapuli, Sriraam Natarajan
Knowledge Graph Alignment using String Edit Distance. CoRR (2020)
Srijita Das, Rishabh K. Iyer, Sriraam Natarajan
Cost Aware Feature Elicitation. KiML@KDD (2020)
Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, Sriraam Natarajan
Non-Parametric Learning of Gaifman Models. CoRR (2020)
Yuqiao Chen, Yibo Yang, Sriraam Natarajan, Nicholas Ruozzi
Lifted Hybrid Variational Inference. IJCAI (2020)
Devendra Singh Dhami, Mayukh Das, Sriraam Natarajan
Knowledge Intensive Learning of Generative Adversarial Networks. KiML@KDD (2020)
Navdeep Kaur, Gautam Kunapuli, Sriraam Natarajan
Non-Parametric Learning of Lifted Restricted Boltzmann Machines. CoRR (2020)
Yan Liu, Sriraam Natarajan
The Best of SIAM Data Mining 2020. Big Data 8 (5) (2020)
Nandini Ramanan, Mayukh Das, Kristian Kersting, Sriraam Natarajan
Discriminative Non-Parametric Learning of Arithmetic Circuits. PGM (2020)
Ashutosh Kakadiya, Sriraam Natarajan, Balaraman Ravindran
Relational Boosted Bandits. CoRR (2020)
Harsha Kokel, Phillip Odom, Shuo Yang, Sriraam Natarajan
A Unified Framework for Knowledge Intensive Gradient Boosting: Leveraging Human Experts for Noisy Sparse Domains. AAAI (2020)
Raksha Kumaraswamy, Nandini Ramanan, Phillip Odom, Sriraam Natarajan
Interactive Transfer Learning in Relational Domains. Künstliche Intell. 34 (2) (2020)
Siwen Yan, Devendra Singh Dhami, Sriraam Natarajan
The Curious Case of Stacking Boosted Relational Dependency Networks. ICBINB@NeurIPS (2020)
Michael A. Skinner, Lakshmi Raman, Neel Shah, Abdelaziz Farhat, Sriraam Natarajan
A Preliminary Approach for Learning Relational Policies for the Management of Critically Ill Children. CoRR (2020)
Yuqiao Chen, Yibo Yang, Sriraam Natarajan, Nicholas Ruozzi
Lifted Hybrid Variational Inference. CoRR (2020)
Srijita Das, Sriraam Natarajan, Kaushik Roy, Ronald Parr, Kristian Kersting
Fitted Q-Learning for Relational Domains. CoRR (2020)
Nandini Ramanan, Sriraam Natarajan
Causal Learning From Predictive Modeling for Observational Data. Frontiers Big Data 3 (2020)
Mayukh Das, Nandini Ramanan, Janardhan Rao Doppa, Sriraam Natarajan
Few-Shot Induction of Generalized Logical Concepts via Human Guidance. Frontiers Robotics AI 7 (2020)
Navdeep Kaur, Gautam Kunapuli, Saket Joshi, Kristian Kersting, Sriraam Natarajan
Neural Networks for Relational Data. CoRR (2019)
Alexander L. Hayes, Mayukh Das, Phillip Odom, Sriraam Natarajan
User Friendly Automatic Construction of Background Knowledge: Mode Construction from ER Diagrams. CoRR (2019)
Fabrizio Riguzzi, Kristian Kersting, Marco Lippi, Sriraam Natarajan
Editorial: Statistical Relational Artificial Intelligence. Frontiers Robotics AI 6 (2019)
Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting, Sriraam Natarajan
Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs. AAAI (2019)
Yuqiao Chen, Nicholas Ruozzi, Sriraam Natarajan
Lifted Message Passing for Hybrid Probabilistic Inference. IJCAI (2019)
Mayukh Das, Devendra Singh Dhami, Yang Yu, Gautam Kunapuli, Sriraam Natarajan
Knowledge-augmented Column Networks: Guiding Deep Learning with Advice. CoRR (2019)
Mayukh Das, Yang Yu, Devendra Singh Dhami, Gautam Kunapuli, Sriraam Natarajan
Human-Guided Learning of Column Networks: Augmenting Deep Learning with Advice. CoRR (2019)
Mayukh Das, Phillip Odom, Md Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan
Planning with actively eliciting preferences. Knowl. Based Syst. 165 (2019)
Navdeep Kaur, Gautam Kunapuli, Saket Joshi, Kristian Kersting, Sriraam Natarajan
Neural Networks for Relational Data. ILP (2019)
Mayukh Das, Nandini Ramanan, Janardhan Rao Doppa, Sriraam Natarajan
One-Shot Induction of Generalized Logical Concepts via Human Guidance. CoRR (2019)
Devendra Singh Dhami, Gautam Kunapuli, David Page, Sriraam Natarajan
Predicting Drug-Drug Interactions from Molecular Structure Images. CoRR (2019)
Phillip Odom, Sriraam Natarajan
Human-Guided Learning for Probabilistic Logic Models. Frontiers Robotics AI 5 (2018)
Mayukh Das, Phillip Odom, Md Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan
Preference-Guided Planning: An Active Elicitation Approach. CoRR (2018)
Erik Blasch, Robert Cruise, Sriraam Natarajan, Ali K. Raz, Tim Kelly
Control Diffusion of Information Collection for Situation Understanding Using Boosting MLNs. FUSION (2018)
Sriraam Natarajan, Srijita Das, Nandini Ramanan, Gautam Kunapuli, Predrag Radivojac
On Whom Should I Perform this Lab Test Next? An Active Feature Elicitation Approach. IJCAI (2018)
Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan
Structure Learning for Relational Logistic Regression: An Ensemble Approach. KR (2018)
Mayukh Das, Phillip Odom, Md Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan
Preference-Guided Planning: An Active Elicitation Approach. AAMAS (2018)
Alejandro Molina, Antonio Vergari, Nicola Di Mauro, Sriraam Natarajan, Floriana Esposito, Kristian Kersting
Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains. AAAI (2018)
Nandini Ramanan, Gautam Kunapuli, Tushar Khot, Bahare Fatemi, Seyed Mehran Kazemi, David Poole, Kristian Kersting, Sriraam Natarajan
Structure Learning for Relational Logistic Regression: An Ensemble Approach. CoRR (2018)
Navdeep Kaur, Gautam Kunapuli, Tushar Khot, Kristian Kersting, William Cohen, Sriraam Natarajan
Relational Restricted Boltzmann Machines: A Probabilistic Logic Learning Approach. ILP (2017)
Alejandro Molina, Antonio Vergari, Nicola Di Mauro, Sriraam Natarajan, Floriana Esposito, Kristian Kersting
Sum-Product Networks for Hybrid Domains. CoRR (2017)
Shuo Yang, Mohammed Korayem, Khalifeh AlJadda, Trey Grainger, Sriraam Natarajan
Combining content-based and collaborative filtering for job recommendation system: A cost-sensitive Statistical Relational Learning approach. Knowl. Based Syst. 136 (2017)
Nandini Ramanan, Shuo Yang, Shaun J. Grannis, Sriraam Natarajan
Discriminative boosted Bayes networks for learning multiple cardiovascular procedures. BIBM (2017)
Noah Hammarlund, Sriraam Natarajan
Does Race Play a Role in Invasive Procedure Treatments? An Initial Analysis. CHASE (2017)
Alejandro Molina, Sriraam Natarajan, Kristian Kersting
Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions. AAAI (2017)
Mayukh Das, Md Rakibul Islam, Janardhan Rao Doppa, Dan Roth, Sriraam Natarajan
Active Preference Elicitation for Planning. AAAI Workshops (2017)
Devendra Singh Dhami, Ameet Soni, David Page, Sriraam Natarajan
Identifying Parkinson's Patients: A Functional Gradient Boosting Approach. AIME (2017)
Sriraam Natarajan, Annu Prabhakar, Nandini Ramanan, Anna N. Baglione, Katie A. Siek, Kay Connelly
Boosting for Postpartum Depression Prediction. CHASE (2017)
Shuo Yang, Fabian Hadiji, Kristian Kersting, Shaun J. Grannis, Sriraam Natarajan
Modeling heart procedures from EHRs: An application of exponential families. BIBM (2017)
Anjali Narayan-Chen, Colin Graber, Mayukh Das, Md Rakibul Islam, Soham Dan, Sriraam Natarajan, Janardhan Rao Doppa, Julia Hockenmaier, Martha Palmer, Dan Roth
Towards Problem Solving Agents that Communicate and Learn. RoboNLP@ACL (2017)
Sriraam Natarajan, Vishal Bangera, Tushar Khot, Jose Picado, Anurag Wazalwar, Vítor Santos Costa, David Page, Michael Caldwell
Markov logic networks for adverse drug event extraction from text. Knowl. Inf. Syst. 51 (2) (2017)
Devendra Singh Dhami, David Leake, Sriraam Natarajan
Knowledge-Based Morphological Classification of Galaxies from Vision Features. AAAI Workshops (2017)
Alexander L. Hayes, Mayukh Das, Phillip Odom, Sriraam Natarajan
User Friendly Automatic Construction of Background Knowledge: Mode Construction from ER Diagrams. K-CAP (2017)
Phillip Odom, Sriraam Natarajan
Actively Interacting with Experts: A Probabilistic Logic Approach. ECML/PKDD (2) (2016)
Phillip Odom, Sriraam Natarajan
Active Advice Seeking for Inverse Reinforcement Learning. AAMAS (2016)
Sriraam Natarajan, Ameet Soni, Anurag Wazalwar, Dileep Viswanathan, Kristian Kersting
Deep Distant Supervision: Learning Statistical Relational Models for Weak Supervision in Natural Language Extraction. Solving Large Scale Learning Tasks (2016)
Ameet Soni, Dileep Viswanathan, Niranjan Pachaiyappan, Sriraam Natarajan
A Comparison of Weak Supervision methods for Knowledge Base Construction. AKBC@NAACL-HLT (2016)
Haley MacLeod, Shuo Yang, Kim Oakes, Kay Connelly, Sriraam Natarajan
Identifying Rare Diseases from Behavioural Data: A Machine Learning Approach. CHASE (2016)
Phillip Odom, Raksha Kumaraswamy, Kristian Kersting, Sriraam Natarajan
Learning Through Advice-Seeking via Transfer. ILP (2016)
Shuo Yang, Tushar Khot, Kristian Kersting, Sriraam Natarajan
Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach. AAAI (2016)
Marcin Malec, Tushar Khot, James G. Nagy, Erik Blask, Sriraam Natarajan
Inductive Logic Programming Meets Relational Databases: Efficient Learning of Markov Logic Networks. ILP (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Sriraam Natarajan