[README] - add gaussian_autoencoder test entry

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
2026-05-30 14:29:25 +02:00
co-authored by Claude Sonnet 4.6
parent b032db3099
commit 3c85705d85
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@@ -18,6 +18,7 @@ These generate their own data and run without external files.
| `test_binary_autoencoder.py` | BB-RBM | Auto-encoder on synthetic bars-and-stripes binary images (8×8). Trains, reconstructs, and plots original vs. reconstruction. | | `test_binary_autoencoder.py` | BB-RBM | Auto-encoder on synthetic bars-and-stripes binary images (8×8). Trains, reconstructs, and plots original vs. reconstruction. |
| `test_model.py` | BB-RBM (4 layers) | Deep auto-encoder on random binary data (1024-dim). Prints per-pattern reconstruction error. | | `test_model.py` | BB-RBM (4 layers) | Deep auto-encoder on random binary data (1024-dim). Prints per-pattern reconstruction error. |
| `test_xor.py` | BB-RBM | Auto-encoder on XOR-like 3-bit patterns using the older `Layer` API. | | `test_xor.py` | BB-RBM | Auto-encoder on XOR-like 3-bit patterns using the older `Layer` API. |
| `test_gaussian_autoencoder.py` | GB-RBM | Auto-encoder on synthetic Gaussian blob images (8×8). Trains, reconstructs, and plots original vs. reconstruction. |
| `test_linear.py` | GB-RBM or GG-RBM | GB/GG-RBM on random continuous data (3000-dim). Toggle `do_gaussian_hidden` at the top of the file. | | `test_linear.py` | GB-RBM or GG-RBM | GB/GG-RBM on random continuous data (3000-dim). Toggle `do_gaussian_hidden` at the top of the file. |
| `test_sub_image.py` | — | Unit test for `SubImage` (patch extraction). No RBM involved. | | `test_sub_image.py` | — | Unit test for `SubImage` (patch extraction). No RBM involved. |
| `test_conv2d.py` | — | Unit test for `conv2d`. No RBM involved. | | `test_conv2d.py` | — | Unit test for `conv2d`. No RBM involved. |