Search Results for author: Ryan Soklaski

Found 3 papers, 1 papers with code

Fourier-Based Augmentations for Improved Robustness and Uncertainty Calibration

no code implementations24 Feb 2022 Ryan Soklaski, Michael Yee, Theodoros Tsiligkaridis

Diverse data augmentation strategies are a natural approach to improving robustness in computer vision models against unforeseen shifts in data distribution.

Image Augmentation

Tools and Practices for Responsible AI Engineering

no code implementations14 Jan 2022 Ryan Soklaski, Justin Goodwin, Olivia Brown, Michael Yee, Jason Matterer

Responsible Artificial Intelligence (AI) - the practice of developing, evaluating, and maintaining accurate AI systems that also exhibit essential properties such as robustness and explainability - represents a multifaceted challenge that often stretches standard machine learning tooling, frameworks, and testing methods beyond their limits.

Adversarial Robustness

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