Ayush Chopra

TL;DR: In this paper, a simulation agent-based modeling study was conducted to estimate population health outcomes with delayed second dose versus standard schedule of SARS-CoV-2 mRNA vaccination.

TL;DR: This work introduces a multi-stage coarse-to-fine warping network to better model fine grained intricacies (while transforming the try-on cloth) and train it with a novel perceptual geometric matching loss to improve the texture transfer network.

TL;DR: This work proposes to jointly predict the support and query masks to force the support features to share characteristics with the query features, and presents a framework - SimPropNet - to bridge gaps in the utilization of this similarity information in existing methods.

TL;DR: A Grid Search Network (GSN) for learning feature embeddings for fashion retrieval significantly outperforms existing state-of-art methods on benchmark fashion datasets and extends the reinforcement learning based strategy to learn custom kernel functions for SVM based classification over FashionMNIST and MNIST datasets, showing improved performance.

TL;DR: This work proposes to use auxiliary learning to power an existing state-of-the-art virtual try-on network and leverage prediction of human semantic segmentation as an auxiliary task and shows that it allows the network to better model the bounds of the clothing item and human skin, thereby producing a better fit.