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Sahil Sidheekh
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2020 – today
- 2024
- [j2]Aroof Aimen
, Sahil Sidheekh
Adaptation: Blessing or Curse for Higher Way Meta-Learning. IEEE Trans. Artif. Intell. 5(4): 1844-1856 (2024) - [c9]Sahil Sidheekh
Deep Tractable Probabilistic Models. COMAD/CODS 2024: 501-504 - [c8]Sahil Sidheekh, Pranuthi Tenali, Saurabh Mathur, Erik Blasch, Sriraam Natarajan:
On the Robustness and Reliability of Late Multi-Modal Fusion using Probabilistic Circuits. FUSION 2024: 1-8 - [c7]Sahil Sidheekh, Sriraam Natarajan:
Building Expressive and Tractable Probabilistic Generative Models: A Review. IJCAI 2024: 8234-8243 - [i10]Sahil Sidheekh, Sriraam Natarajan:
Building Expressive and Tractable Probabilistic Generative Models: A Review. CoRR abs/2402.00759 (2024) - [i9]Sahil Sidheekh, Pranuthi Tenali, Saurabh Mathur, Erik Blasch, Kristian Kersting, Sriraam Natarajan:
Credibility-Aware Multi-Modal Fusion Using Probabilistic Circuits. CoRR abs/2403.03281 (2024) - [i8]Athresh Karanam, Saurabh Mathur, Sahil Sidheekh, Sriraam Natarajan:
A Unified Framework for Human-Allied Learning of Probabilistic Circuits. CoRR abs/2405.02413 (2024) - 2023
- [j1]Aroof Aimen
Leveraging Task Variability in Meta-learning. SN Comput. Sci. 4(5): 539 (2023) - [c6]Sahil Sidheekh, Kristian Kersting, Sriraam Natarajan:
Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference. UAI 2023: 1964-1973 - 2022
- [c5]Sahil Sidheekh, Chris B. Dock, Tushar Jain, Radu V. Balan, Maneesh Kumar Singh:
VQ-Flows: Vector quantized local normalizing flows. UAI 2022: 1835-1845 - [i7]Sahil Sidheekh, Chris B. Dock, Tushar Jain, Radu V. Balan, Maneesh Kumar Singh:
VQ-Flows: Vector Quantized Local Normalizing Flows. CoRR abs/2203.11556 (2022) - 2021
- [c4]Aroof Aimen, Sahil Sidheekh, Vineet Madan, Narayanan C. Krishnan:
Stress Testing of Meta-learning Approaches for Few-shot Learning. MetaDL@AAAI 2021: 38-44 - [c3]Sahil Sidheekh, Aroof Aimen, Narayanan C. Krishnan:
On Characterizing GAN Convergence Through Proximal Duality Gap. ICML 2021: 9660-9670 - [c2]Sahil Sidheekh, Aroof Aimen
On Duality Gap as a Measure for Monitoring GAN Training. IJCNN 2021: 1-8 - [i6]Sahil Sidheekh:
Learning Neural Networks on SVD Boosted Latent Spaces for Semantic Classification. CoRR abs/2101.00563 (2021) - [i5]Aroof Aimen, Sahil Sidheekh, Vineet Madan, Narayanan C. Krishnan:
Stress Testing of Meta-learning Approaches for Few-shot Learning. CoRR abs/2101.08587 (2021) - [i4]Sahil Sidheekh, Aroof Aimen, Narayanan C. Krishnan:
Characterizing GAN Convergence Through Proximal Duality Gap. CoRR abs/2105.04801 (2021) - [i3]Aroof Aimen, Sahil Sidheekh, Narayanan C. Krishnan:
Task Attended Meta-Learning for Few-Shot Learning. CoRR abs/2106.10642 (2021) - [i2]Avideep Mukherjee, Badri Narayana Patro, Sahil Sidheekh, Maneesh Singh, Vinay P. Namboodiri:
Attentive Contractive Flow: Improved Contractive Flows with Lipschitz-constrained Self-Attention. CoRR abs/2109.12135 (2021) - 2020
- [c1]Aroof Aimen
Scale Invariant Fast PHT based Copy-Move Forgery Detection. ICCCNT 2020: 1-7 - [i1]Sahil Sidheekh, Aroof Aimen, Vineet Madan, Narayanan C. Krishnan:
On Duality Gap as a Measure for Monitoring GAN Training. CoRR abs/2012.06723 (2020)
Coauthor Index
aka: Narayanan C. Krishnan
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