Natarajan, Sriraam

49 publications

AAAI 2025 A Unified Framework for Human-Allied Learning of Probabilistic Circuits Athresh Karanam, Saurabh Mathur, Sahil Sidheekh, Sriraam Natarajan

AISTATS 2025 Credibility-Aware Multimodal Fusion Using Probabilistic Circuits Sahil Sidheekh, Pranuthi Tenali, Saurabh Mathur, Erik Blasch, Kristian Kersting, Sriraam Natarajan

AAAI 2025 Human-in-the-Loop or AI-in-the-Loop? Automate or Collaborate? Sriraam Natarajan, Saurabh Mathur, Sahil Sidheekh, Wolfgang Stammer, Kristian Kersting

TMLR 2025 Tractable Representation Learning with Probabilistic Circuits Steven Braun, Sahil Sidheekh, Antonio Vergari, Martin Mundt, Sriraam Natarajan, Kristian Kersting

IJCAI 2024 Building Expressive and Tractable Probabilistic Generative Models: A Review Sahil Sidheekh, Sriraam Natarajan

MLJ 2024 Explainable Models via Compression of Tree Ensembles Siwen Yan, Sriraam Natarajan, Saket Joshi, Roni Khardon, Prasad Tadepalli

UAI 2024 Knowledge Intensive Learning of Credal Networks Saurabh Mathur, Alessandro Antonucci, Sriraam Natarajan

AAAI 2024 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

AAAI 2024 Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, Thirty-Sixth Conference on Innovative Applications of Artificial Intelligence, IAAI 2024, Fourteenth Symposium on Educational Advances in Artificial Intelligence, EAAI 2014, February 20-27, 2024, Vancouver, Canada Michael J. Wooldridge, Jennifer G. Dy, Sriraam Natarajan

UAI 2023 Knowledge Intensive Learning of Cutset Networks Saurabh Mathur, Vibhav Gogate, Sriraam Natarajan

UAI 2023 Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference Sahil Sidheekh, Kristian Kersting, Sriraam Natarajan

AISTATS 2022 Relational Neural Markov Random Fields Yuqiao Chen, Sriraam Natarajan, Nicholas Ruozzi

PGM 2022 Explaining Deep Tractable Probabilistic Models: The Sum-Product Network Case Bhagirath Athresh Karanam, Saurabh Mathur, Predrag Radivojac, David M Haas, Kristian Kersting, Sriraam Natarajan

NeurIPSW 2021 Deep RePReL--Combining Planning and Deep RL for Acting in Relational Domains Harsha Kokel, Arjun Manoharan, Sriraam Natarajan, Balaraman Ravindran, Prasad Tadepalli

NeurIPS 2021 Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models Matej Zečević, Devendra Dhami, Athresh Karanam, Sriraam Natarajan, Kristian Kersting

AAAI 2021 Relational Boosted Bandits Ashutosh Kakadiya, Sriraam Natarajan, Balaraman Ravindran

PGM 2020 Discriminative Non-Parametric Learning of Arithmetic Circuits Nandini Ramanan, Mayukh Das, Kristian Kersting, Sriraam Natarajan

AAAI 2020 A Unified Framework for Knowledge Intensive Gradient Boosting: Leveraging Human Experts for Noisy Sparse Domains Harsha Kokel, Phillip Odom, Shuo Yang, Sriraam Natarajan

IJCAI 2020 Lifted Hybrid Variational Inference Yuqiao Chen, Yibo Yang, Sriraam Natarajan, Nicholas Ruozzi

NeurIPSW 2020 The Curious Case of Stacking Boosted Relational Dependency Networks Siwen Yan, Devendra Singh Dhami, Sriraam Natarajan

AAAI 2019 Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs Mayukh Das, Devendra Singh Dhami, Gautam Kunapuli, Kristian Kersting, Sriraam Natarajan

IJCAI 2019 Lifted Message Passing for Hybrid Probabilistic Inference Yuqiao Chen, Nicholas Ruozzi, Sriraam Natarajan

AAAI 2018 Mixed Sum-Product Networks: A Deep Architecture for Hybrid Domains Alejandro Molina, Antonio Vergari, Nicola Di Mauro, Sriraam Natarajan, Floriana Esposito, Kristian Kersting

IJCAI 2018 On Whom Should I Perform This Lab Test Next? an Active Feature Elicitation Approach Sriraam Natarajan, Srijita Das, Nandini Ramanan, Gautam Kunapuli, Predrag Radivojac

AAAI 2017 Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions Alejandro Molina, Sriraam Natarajan, Kristian Kersting

ECML-PKDD 2016 Actively Interacting with Experts: A Probabilistic Logic Approach Phillip Odom, Sriraam Natarajan

AAAI 2016 Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach Shuo Yang, Tushar Khot, Kristian Kersting, Sriraam Natarajan

AAAI 2015 Active Advice Seeking for Inverse Reinforcement Learning Phillip Odom, Sriraam Natarajan

MLJ 2015 Gradient-Based Boosting for Statistical Relational Learning: The Markov Logic Network and Missing Data Cases Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik

AAAI 2015 Knowledge-Based Probabilistic Logic Learning Phillip Odom, Tushar Khot, Reid B. Porter, Sriraam Natarajan

AAAI 2015 Learning to Reject Sequential Importance Steps for Continuous-Time Bayesian Networks Jeremy C. Weiss, Sriraam Natarajan, C. David Page Jr.

MLJ 2015 Poisson Dependency Networks: Gradient Boosted Models for Multivariate Count Data Fabian Hadiji, Alejandro Molina, Sriraam Natarajan, Kristian Kersting

JAIR 2014 A Decision-Theoretic Model of Assistance Alan Fern, Sriraam Natarajan, Kshitij Judah, Prasad Tadepalli

AAAI 2014 Relational One-Class Classification: A Non-Parametric Approach Tushar Khot, Sriraam Natarajan, Jude W. Shavlik

ECML-PKDD 2013 AR-Boost: Reducing Overfitting by a Robust Data-Driven Regularization Strategy Baidya Nath Saha, Gautam Kunapuli, Nilanjan Ray, Joseph A. Maldjian, Sriraam Natarajan

MLJ 2013 Exploiting Symmetries for Scaling Loopy Belief Propagation and Relational Training Babak Ahmadi, Kristian Kersting, Martin Mladenov, Sriraam Natarajan

ECML-PKDD 2013 Knowledge Intensive Learning: Combining Qualitative Constraints with Causal Independence for Parameter Learning in Probabilistic Models Shuo Yang, Sriraam Natarajan

MLJ 2012 Gradient-Based Boosting for Statistical Relational Learning: The Relational Dependency Network Case Sriraam Natarajan, Tushar Khot, Kristian Kersting, Bernd Gutmann, Jude W. Shavlik

AAAI 2012 Identifying Adverse Drug Events by Relational Learning David Page, Vítor Santos Costa, Sriraam Natarajan, Aubrey Barnard, Peggy L. Peissig, Michael Caldwell

ECML-PKDD 2012 Lifted Online Training of Relational Models with Stochastic Gradient Methods Babak Ahmadi, Kristian Kersting, Sriraam Natarajan

NeurIPS 2012 Multiplicative Forests for Continuous-Time Processes Jeremy Weiss, Sriraam Natarajan, David Page

IJCAI 2011 Imitation Learning in Relational Domains: A Functional-Gradient Boosting Approach Sriraam Natarajan, Saket Joshi, Prasad Tadepalli, Kristian Kersting, Jude W. Shavlik

ECML-PKDD 2010 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

UAI 2009 Counting Belief Propagation Kristian Kersting, Babak Ahmadi, Sriraam Natarajan

IJCAI 2009 Speeding up Inference in Markov Logic Networks by Preprocessing to Reduce the Size of the Resulting Grounded Network Jude W. Shavlik, Sriraam Natarajan

MLJ 2008 Transfer in Variable-Reward Hierarchical Reinforcement Learning Neville Mehta, Sriraam Natarajan, Prasad Tadepalli, Alan Fern

IJCAI 2007 A Decision-Theoretic Model of Assistance Alan Fern, Sriraam Natarajan, Kshitij Judah, Prasad Tadepalli

ICML 2005 Dynamic Preferences in Multi-Criteria Reinforcement Learning Sriraam Natarajan, Prasad Tadepalli

ICML 2005 Learning First-Order Probabilistic Models with Combining Rules Sriraam Natarajan, Prasad Tadepalli, Eric Altendorf, Thomas G. Dietterich, Alan Fern, Angelo C. Restificar