May 2022 – July 2022
Aug 2019 - Sep 2019
A training tool to help chess players test their positional understanding.
In this work, we propose distinct model-agnostic benchmark perturbations of images in order to investigate the resilience and robustness of different network architectures. Our findings provide direction for future understanding of residual connections and depth on network robustness.arXiv
Aug 2020 – Jan 2021
May 2019 - Jul 2019
Deep convolutional conditional GAN implementation with CelebA dataset that allows for generation of custom faces according to textual input.