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license: apache-2.0
tags:
- pytorch
- mechanistic-interpretability
- gravitational-lensing
- physics-informed
- equivariant
- computer-vision
- d4-symmetry
---
# D4LensPINN Weights
This repository contains the trained checkpoints for the D4LensPINN
gravitational lens classification model and its ResNet-18 baseline.
## Checkpoints
- `d4phase2best.pth`: Best D4LensPINN checkpoint.
- `resnet18baseline_best.pth`: ResNet-18 baseline checkpoint.
## Intended Use
These weights are provided for reproducibility and research use in
mechanistic interpretability experiments on hybrid physics-ML
architectures.
## Notes
- Inputs are 150×150 grayscale images.
- D4LensPINN expects the full physics pipeline described in the paper.
- The checkpoint files are not meant to be used as standalone generic
image classifiers without the corresponding model code.
## Loading
Example:
```python
import torch
ckpt = torch.load("d4phase2best.pth", map_location="cpu")
```
The exact model class definitions must match the training code used to
create the checkpoints.
## Reproducibility
If you use these weights, please cite the associated paper.
## License
Apache-2.0 License. |