---
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.