DGNO — Discontinuous Galerkin Neural Operator
Pretrained checkpoints and the preprocessed BBBC006 dataset for "Discontinuous Galerkin Neural Operator for Pathology Defocus Deblurring" (ICML 2026).
- Code & full usage: https://github.com/Duane245/DGNO
- Task: microscopy / pathology defocus deblurring
DGNO comes in two operator variants — DGNO-Face (face-wise discontinuous Galerkin operator) and DGNO-Cell (cell-wise) — both produced by a single training architecture and loaded by a unified evaluation architecture for inference.
Checkpoints
Six checkpoints — three datasets × two variants. Each .pth stores both the raw weights
(params) and the EMA weights (params_ema).
| Dataset | DGNO-Face | DGNO-Cell |
|---|---|---|
| BBBC006 w1 | pretrained/DGNO_BBBC006_w1_Face.pth |
pretrained/DGNO_BBBC006_w1_Cell.pth |
| BBBC006 w2 | pretrained/DGNO_BBBC006_w2_Face.pth |
pretrained/DGNO_BBBC006_w2_Cell.pth |
| 3DHistech | pretrained/DGNO_3DHistech_Face.pth |
pretrained/DGNO_3DHistech_Cell.pth |
Download all six into pretrained/:
pip install -U huggingface_hub
huggingface-cli download Duane245/DGNO --include "pretrained/*" --local-dir .
Or a single checkpoint:
huggingface-cli download Duane245/DGNO pretrained/DGNO_3DHistech_Face.pth --local-dir .
BBBC006 dataset
BBBC006.tar.gz (~3.4 GB) is the preprocessed BBBC006 set used in the paper — fluorescence
microscopy, single-channel grayscale, with both the w1 (Hoechst-stained nuclei) and w2
(Phalloidin-stained actin) channels in one archive.
huggingface-cli download Duane245/DGNO BBBC006.tar.gz --local-dir datasets
tar -xzf datasets/BBBC006.tar.gz -C datasets && rm datasets/BBBC006.tar.gz
Extraction yields datasets/BBBC006/{train,test}/{GT,blur}/*.tif, ready for training and
testing with no further preprocessing; the w1 / w2 split is selected at run time.
Results
| Dataset | Variant | PSNR ↑ | SSIM ↑ | LPIPS ↓ |
|---|---|---|---|---|
| BBBC006 w1 | DGNO-Cell | 37.22 | 0.959 | 0.103 |
| BBBC006 w1 | DGNO-Face | 37.09 | 0.958 | 0.104 |
| BBBC006 w2 | DGNO-Face | 32.66 | 0.847 | 0.323 |
| BBBC006 w2 | DGNO-Cell | 32.54 | 0.848 | 0.322 |
| 3DHistech | DGNO-Face | 34.02 | 0.890 | 0.095 |
| 3DHistech | DGNO-Cell | 34.00 | 0.890 | 0.093 |
License
Apache-2.0. BBBC006 imagery originates from the Broad Bioimage Benchmark Collection. See the GitHub repository for the citation and details.