Search Results for author: Orion Reblitz-Richardson

Found 6 papers, 3 papers with code

Convolutional Networks are Inherently Foveated

no code implementations NeurIPS Workshop SVRHM 2021 Bilal Alsallakh, Vivek Miglani, Narine Kokhlikyan, David Adkins, Orion Reblitz-Richardson

When convolutional layers apply no padding, central pixels have more ways to contribute to the convolution than peripheral pixels.

Foveation

Investigating Saturation Effects in Integrated Gradients

1 code implementation23 Oct 2020 Vivek Miglani, Narine Kokhlikyan, Bilal Alsallakh, Miguel Martin, Orion Reblitz-Richardson

We explore these effects and find that gradients in saturated regions of this path, where model output changes minimally, contribute disproportionately to the computed attribution.

Captum: A unified and generic model interpretability library for PyTorch

2 code implementations16 Sep 2020 Narine Kokhlikyan, Vivek Miglani, Miguel Martin, Edward Wang, Bilal Alsallakh, Jonathan Reynolds, Alexander Melnikov, Natalia Kliushkina, Carlos Araya, Siqi Yan, Orion Reblitz-Richardson

The library contains generic implementations of a number of gradient and perturbation-based attribution algorithms, also known as feature, neuron and layer importance algorithms, as well as a set of evaluation metrics for these algorithms.

Feature Importance

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