Scale Invariant Fast PHT based Copy-Move Forgery Detection. - Aroof Aimen; Amandeep Kaur; Sahil Sidheekh (ICCCNT, 2020)

Stress Testing of Meta-learning Approaches for Few-shot Learning. - Aroof Aimen; Sahil Sidheekh; Vineet Madan; Narayanan C. Krishnan (MetaDL@AAAI, 2021)

On Characterizing GAN Convergence Through Proximal Duality Gap. - Sahil Sidheekh; Aroof Aimen; Narayanan C. Krishnan (ICML, 2021)

On Duality Gap as a Measure for Monitoring GAN Training. - Sahil Sidheekh; Aroof Aimen; Vineet Madan; Narayanan C. Krishnan (IJCNN, 2021)

Learning Neural Networks on SVD Boosted Latent Spaces for Semantic Classification. - Sahil Sidheekh (CoRR, 2021)

Task Attended Meta-Learning for Few-Shot Learning. - Aroof Aimen; Sahil Sidheekh; Narayanan C. Krishnan (CoRR, 2021)

Attentive Contractive Flow: Improved Contractive Flows with Lipschitz-constrained Self-Attention. - Avideep Mukherjee; Badri Narayana Patro; Sahil Sidheekh; Maneesh Singh 001; Vinay P. Namboodiri (CoRR, 2021)

VQ-Flows: Vector quantized local normalizing flows. - Sahil Sidheekh; Chris B. Dock; Tushar Jain; Radu V. Balan; Maneesh Kumar Singh 001 (UAI, 2022)

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

Leveraging Task Variability in Meta-learning. - Aroof Aimen; Bharat Ladrecha; Sahil Sidheekh; Narayanan C. Krishnan (SN Comput. Sci., 2023)

Deep Tractable Probabilistic Models. - Sahil Sidheekh; Saurabh Mathur 002; Athresh Karanam; Sriraam Natarajan (COMAD/CODS, 2024)

On the Robustness and Reliability of Late Multi-Modal Fusion using Probabilistic Circuits. - Sahil Sidheekh; Pranuthi Tenali; Saurabh Mathur 002; Erik Blasch; Sriraam Natarajan (FUSION, 2024)

Building Expressive and Tractable Probabilistic Generative Models: A Review. - Sahil Sidheekh; Sriraam Natarajan (IJCAI, 2024)

Credibility-Aware Multi-Modal Fusion Using Probabilistic Circuits. - Sahil Sidheekh; Pranuthi Tenali; Saurabh Mathur 002; Erik Blasch; Kristian Kersting; Sriraam Natarajan (CoRR, 2024)

Adaptation: Blessing or Curse for Higher Way Meta-Learning. - Aroof Aimen; Sahil Sidheekh; Bharat Ladrecha; Hansin Ahuja; Narayanan C. Krishnan (IEEE Trans. Artif. Intell., 2024)

A Unified Framework for Human-Allied Learning of Probabilistic Circuits. - Athresh Karanam; Saurabh Mathur 002; Sahil Sidheekh; Sriraam Natarajan (AAAI, 2025)

Human-in-the-loop or AI-in-the-loop? Automate or Collaborate? - Sriraam Natarajan; Saurabh Mathur 002; Sahil Sidheekh; Wolfgang Stammer; Kristian Kersting (AAAI, 2025)

Credibility-Aware Multimodal Fusion Using Probabilistic Circuits. - Sahil Sidheekh; Pranuthi Tenali; Saurabh Mathur 002; Erik Blasch; Kristian Kersting; Sriraam Natarajan (AISTATS, 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 023; Gregory D. Larsen; Miles R. Silman; Luis Fernendez; Robert J. Plemmons; Sriraam Natarajan; V. Paul Pauca (PAKDD (2), 2025)

Tractable Representation Learning with Probabilistic Circuits. - Steven Braun; Sahil Sidheekh; Antonio Vergari; Martin Mundt; Sriraam Natarajan; Kristian Kersting (CoRR, 2025)

Tractable Sharpness-Aware Learning of Probabilistic Circuits. - Hrithik Suresh; Sahil Sidheekh; Vishnu Shreeram M. P; Sriraam Natarajan; Narayanan C. Krishnan (CoRR, 2025)