5 citations · 8 across the 6 of their papers we have counts for
7 papers
VQ-Flows: Vector Quantized Local Normalizing Flows
Sahil Sidheekh, Chris B. Dock, Tushar Jain +2
Normalizing flows provide an elegant approach to generative modeling that allows for efficient sampling and exact density evaluation of unknown data distributions. However, current…
Attentive Contractive Flow with Lipschitz-constrained Self-Attention
Avideep Mukherjee, Badri Narayan Patro, Vinay P. Namboodiri
Normalizing flows provide an elegant method for obtaining tractable density estimates from distributions by using invertible transformations. The main challenge is to improve the e…
Task Attended Meta-Learning for Few-Shot Learning
Aroof Aimen, Sahil Sidheekh, Narayanan C. Krishnan
Meta-learning (ML) has emerged as a promising direction in learning models under constrained resource settings like few-shot learning. The popular approaches for ML either learn a…
On Characterizing GAN Convergence Through Proximal Duality Gap
Sahil Sidheekh, Aroof Aimen, Narayanan C. Krishnan
Despite the accomplishments of Generative Adversarial Networks (GANs) in modeling data distributions, training them remains a challenging task. A contributing factor to this diffic…
Stress Testing of Meta-learning Approaches for Few-shot Learning
Aroof Aimen, Sahil Sidheekh, Vineet Madan +1
Meta-learning (ML) has emerged as a promising learning method under resource constraints such as few-shot learning. ML approaches typically propose a methodology to learn generaliz…
Learning Neural Networks on SVD Boosted Latent Spaces for Semantic Classification
Sahil Sidheekh
The availability of large amounts of data and compelling computation power have made deep learning models much popular for text classification and sentiment analysis. Deep neural n…
On Duality Gap as a Measure for Monitoring GAN Training
Sahil Sidheekh, Aroof Aimen, Vineet Madan +1
Generative adversarial network (GAN) is among the most popular deep learning models for learning complex data distributions. However, training a GAN is known to be a challenging ta…