Spatial Neural Feature Accentuation checkpoints
Files
| File | Purpose | SHA-256 |
|---|
resnet50_robust_backbone.pt | Adversarially robust ImageNet ResNet-50 state dict | 6c6731b622d6e521d4e36707f5a0d24d18ff7d8ffee1ac30b7a68eb36871c763 |
resnet50_robust_25_compiled_targets.pt | 25 PCA/readout objectives collapsed to feature-space weights and biases | 69975cfdf5abaaecfaf34ea76d05b02f93bc2d4f13a195d99b3652a1f7b24757 |
The compiled cache contains five selected neural-encoding targets for each of
five monkeys (leap, paul, red, three0, and venus). Internal filesystem
paths have been removed from this publication copy. It retains target IDs,
subject labels, unit IDs, robust-ResNet layer names, effective weights/biases,
and q01/q99 response normalization values.
Use
The companion repository downloads these files at a pinned Hub revision and
checks both SHA-256 hashes before loading them. They can also be downloaded with:
1hf download binxu/spatial-neural-feature-accentuation-checkpoints \
2 --include 'resnet50_robust_*.pt' \
3 --local-dir checkpoints
These files are intended for differentiable feature visualization and the
research-art workflow documented in the companion repository. The 25 compiled
targets are not general-purpose image classifiers.
Licenses and provenance
The companion code is MIT licensed. These weight artifacts retain the terms of
their original models and source data; users are responsible for complying with
those terms. See the companion repository for method details, limitations,
privacy guidance, target definitions, and reproducibility metadata.
