19 citations · 36 across the 18 of their papers we have counts for
5 papers · 1 filter
Sakana Fugu Technical Report
Yujin Tang, Edoardo Cetin, Jinglue Xu +11
The capabilities of frontier Large Language Models (LLMs) continue to advance, with different providers increasingly specializing in distinct domains. This raises a natural next ob…
k* Distribution: Evaluating the Latent Space of Deep Neural Networks using Local Neighborhood Analysis
Shashank Kotyan, Tatsuya Ueda, Danilo Vasconcellos Vargas
Most examinations of neural networks' learned latent spaces typically employ dimensionality reduction techniques such as t-SNE or UMAP. These methods distort the local neighborhood…
Towards Improving Robustness Against Common Corruptions using Mixture of Class Specific Experts
Shashank Kotyan, Danilo Vasconcellos Vargas
Neural networks have demonstrated significant accuracy across various domains, yet their vulnerability to subtle input alterations remains a persistent challenge. Conventional meth…
A reading survey on adversarial machine learning: Adversarial attacks and their understanding
Shashank Kotyan
Deep Learning has empowered us to train neural networks for complex data with high performance. However, with the growing research, several vulnerabilities in neural networks have…
Adversarial Robustness Assessment: Why both and Attacks Are Necessary
Shashank Kotyan, Danilo Vasconcellos Vargas
There exists a vast number of adversarial attacks and defences for machine learning algorithms of various types which makes assessing the robustness of algorithms a daunting task.…