4 citations · 6 across the 2 of their papers we have counts for
5 papers
Investigating Power laws in Deep Representation Learning
Arna Ghosh, Arnab Kumar Mondal, Kumar Krishna Agrawal +1
Representation learning that leverages large-scale labelled datasets, is central to recent progress in machine learning. Access to task relevant labels at scale is often scarce or…
Mini-batch graphs for robust image classification
Arnab Kumar Mondal, Vineet Jain, Kaleem Siddiqi
Current deep learning models for classification tasks in computer vision are trained using mini-batches. In the present article, we take advantage of the relationships between samp…
Group Equivariant Deep Reinforcement Learning
Arnab Kumar Mondal, Pratheeksha Nair, Kaleem Siddiqi
In Reinforcement Learning (RL), Convolutional Neural Networks(CNNs) have been successfully applied as function approximators in Deep Q-Learning algorithms, which seek to learn acti…
Few-shot 3D Multi-modal Medical Image Segmentation using Generative Adversarial Learning
Arnab Kumar Mondal, Jose Dolz, Christian Desrosiers
We address the problem of segmenting 3D multi-modal medical images in scenarios where very few labeled examples are available for training. Leveraging the recent success of adversa…
Retinal Vessel Segmentation under Extreme Low Annotation: A Generative Adversarial Network Approach
Avisek Lahiri, Vineet Jain, Arnab Mondal +1
Contemporary deep learning based medical image segmentation algorithms require hours of annotation labor by domain experts. These data hungry deep models perform sub-optimally in t…