Sahil Sidheekh

According to our database, Sahil Sidheekh authored at least 16 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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., April, 2024

A Unified Framework for Human-Allied Learning of Probabilistic Circuits.

Athresh Karanam, Saurabh Mathur, Sahil Sidheekh, Sriraam Natarajan

CoRR, 2024

Credibility-Aware Multi-Modal Fusion Using Probabilistic Circuits.

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

CoRR, 2024

Building Expressive and Tractable Probabilistic Generative Models: A Review.

Sahil Sidheekh, Sriraam Natarajan

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

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

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

Proceedings of the 27th International Conference on Information Fusion, 2024

Deep Tractable Probabilistic Models.

Sahil Sidheekh, Saurabh Mathur, Athresh Karanam, Sriraam Natarajan

Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD), 2024

2023

Leveraging Task Variability in Meta-learning.

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

SN Comput. Sci., September, 2023

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

Sahil Sidheekh, Kristian Kersting, Sriraam Natarajan

Proceedings of the Uncertainty in Artificial Intelligence, 2023

2022

VQ-Flows: Vector quantized local normalizing flows.

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

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Attentive Contractive Flow: Improved Contractive Flows with Lipschitz-constrained Self-Attention.

Avideep Mukherjee, Badri Narayana Patro, Sahil Sidheekh, Maneesh Singh, Vinay P. Namboodiri

CoRR, 2021

Task Attended Meta-Learning for Few-Shot Learning.

Aroof Aimen, Sahil Sidheekh, Narayanan C. Krishnan

CoRR, 2021

Learning Neural Networks on SVD Boosted Latent Spaces for Semantic Classification.

Sahil Sidheekh

CoRR, 2021

On Duality Gap as a Measure for Monitoring GAN Training.

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

Proceedings of the International Joint Conference on Neural Networks, 2021

On Characterizing GAN Convergence Through Proximal Duality Gap.

Sahil Sidheekh, Aroof Aimen, Narayanan C. Krishnan

Proceedings of the 38th International Conference on Machine Learning, 2021

Stress Testing of Meta-learning Approaches for Few-shot Learning.

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

Proceedings of the AAAI Workshop on Meta-Learning and MetaDL Challenge, 2021

2020

Scale Invariant Fast PHT based Copy-Move Forgery Detection.

Aroof Aimen, Amandeep Kaur, Sahil Sidheekh

Proceedings of the 11th International Conference on Computing, 2020