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Matgc04/neuralatlas-attributions-resnet101

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Citation text from the card

Precomputed attribution maps and faithfulness metrics for the torchvision
`resnet101` model (default pretrained weights, no fine-tuning) on `imagenet-pico`,
a 3000-image subset of ImageNet-1k with three images for each of the 1000
classes.

This repository is part of **Neural Atlas**, a web tool for comparing
attribution methods across vision architectures on the same image, developed
as an undergraduate thesis at the Facultad de Informática, Universidad
Nacional de La Plata (Argentina). The viewer reads these files directly; they
can also be used on their own, without the tool.

- Code: <https://github.com/midusi/NeuralAtlas>
- Author: Matías Gómez Carrique
- Advisors: Dr. Franco Ronchetti, Dr. Facundo Manuel Quiroga, Mg. Oscar Agustín Stanchi

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dataset_licence({ "id": "Matgc04/neuralatlas-attributions-resnet101" })
signal: "restrictive"
stated_licence: "cc-by-nc-4.0"
sources: 0