Sahil Sidheekh

Tractable and expressive generative modeling with probabilistic flow circuits

Sahil Sidheekh and Sriraam Natarajan

Neurosymbolic AI: Foundations and Applications, pages 183–222. Wiley Online Library, 2026.

Tractable Sharpness-Aware Learning of Probabilistic Circuits

Sahil Sidheekh, Hrithik Suresh, Vishnu Shreeram, Sriraam Natarajan, Narayanan C. Krishnan

The 40th Annual AAAI Conference on Artificial Intelligence (AAAI), 2026

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

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

The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025

Credibility-Aware Multi-Modal Fusion Using Probabilistic Circuits

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

The 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 2025

A Unified Framework for Human-Allied Learning of Probabilistic Circuits

Sahil Sidheekh, Athresh Karanam, Saurabh Mathur, Sriraam Natarajan

The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025

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, Greg Larsen, Miles Silman, Luis Fernendez, Robert Plemmons, Sriraam Natarajan, V. Paul Pauca

The 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2025

Human-Allied Relational Reinforcement Learning

FG Darvishvand, H Shindo, Sahil Sidheekh, Kristian Kersting, Sriraam Natarajan

The Twelfth Annual Conference on Advances in Cognitive Systems (ACS), 2025

Building Expressive and Tractable Probabilistic Generative Models: A Review

Sahil Sidheekh, Sriraam Natarajan

The 33rd International Joint Conference on Artificial Intelligence (IJCAI), 2024

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

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

The 27th International Conference on Information Fusion (FUSION), 2024

Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference

Sahil Sidheekh, Kristian Kersting, Sriraam Natarajan

The 39th Conference on Uncertainty in Artificial Intelligence (UAI), 2023

VQ-Flows: Vector Quantized Local Normalizing Flows

Sahil Sidheekh, Chris B. Dock, Tushar Jain, Radu Balan, Maneesh K. Singh

The 38th Conference on Uncertainty in Artificial Intelligence (UAI), 2022

On Characterizing GAN Convergence Through Proximal Duality Gap

Sahil Sidheekh, Aroof Aimen, Narayanan C. Krishnan

Proceedings of the 38th International Conference on Machine Learning (ICML), PMLR 139, 9660–9670, 2021

On Duality Gap as a Measure for Monitoring GAN Training

Sahil Sidheekh, Aroof Aimen, Vineet Madan, Narayanan C. Krishnan

International Joint Conference on Neural Networks (IJCNN), 2021

Tractable Representation Learning with Probabilistic Circuits

Steven Braun, Sahil Sidheekh, Antonio Vergari, Marius Mundt, Sriraam Natarajan, Kristian Kersting

Transactions on Machine Learning Research (TMLR), 2025

Adaptation: Blessing or Curse for Higher Way Meta-Learning

Aroof Aimen, Sahil Sidheekh, Bharat Ladrecha, Hansin Ahuja, Narayanan C. Krishnan

IEEE Transactions on Artificial Intelligence, 5(4), 1844–1856, 2023

Leveraging Task Variability in Meta-Learning

Aroof Aimen, Bharat Ladrecha, Sahil Sidheekh, Narayanan C. Krishnan

SN Computer Science, 4(5), 539. Springer, 2023

EWSmethods: An R Package to Forecast Tipping Points at the Community Level Using Early Warning Signals, Resilience Measures, and Machine Learning Models

Duncan A. O'Brien, Smita Deb, Sahil Sidheekh, Narayanan C. Krishnan, Partha Sharathi Dutta

Ecography, e06674, 2023

Machine Learning Methods Trained on Simple Models Can Predict Critical Transitions in Complex Natural Systems

Smita Deb, Sahil Sidheekh, Christopher F. Clements, Narayanan C. Krishnan, Partha Sharathi Dutta

Royal Society Open Science, 9(2), 211475, 2022

Autoencoding Probabilistic Circuits

Steven Braun, Sahil Sidheekh, Sriraam Natarajan, Antonio Vergari, Marius Mundt, Kristian Kersting

The Eighth Workshop on Tractable Probabilistic Modeling (TPM), 2025

Credibility-Aware Reliable Multi-Modal Fusion Using Probabilistic Circuits

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

The 2nd Workshop on Deployable AI (DAI), co-located at AAAI, 2024

Bayesian Learning of Probabilistic Circuits with Domain Constraints

Sahil Sidheekh, Athresh Karanam, Saurabh Mathur, Sriraam Natarajan

The 6th Workshop on Tractable Probabilistic Modeling (TPM), co-located at UAI, 2023

Stress Testing of Meta-Learning Approaches for Few-Shot Learning

Aroof Aimen, Sahil Sidheekh, Vineet Madan, Narayanan C. Krishnan

AAAI Workshop on Meta-Learning and MetaDL Challenge (MetaDL), PMLR 140, 38–44, 2021

Task Attended Meta-Learning for Few-Shot Learning

Aroof Aimen, Sahil Sidheekh, Narayanan C. Krishnan

The 5th Workshop on Meta-Learning at NeurIPS, 2021