[README] - add gaussian_autoencoder test entry
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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@@ -18,6 +18,7 @@ These generate their own data and run without external files.
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| `test_binary_autoencoder.py` | BB-RBM | Auto-encoder on synthetic bars-and-stripes binary images (8×8). Trains, reconstructs, and plots original vs. reconstruction. |
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| `test_binary_autoencoder.py` | BB-RBM | Auto-encoder on synthetic bars-and-stripes binary images (8×8). Trains, reconstructs, and plots original vs. reconstruction. |
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| `test_model.py` | BB-RBM (4 layers) | Deep auto-encoder on random binary data (1024-dim). Prints per-pattern reconstruction error. |
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| `test_model.py` | BB-RBM (4 layers) | Deep auto-encoder on random binary data (1024-dim). Prints per-pattern reconstruction error. |
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| `test_xor.py` | BB-RBM | Auto-encoder on XOR-like 3-bit patterns using the older `Layer` API. |
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| `test_xor.py` | BB-RBM | Auto-encoder on XOR-like 3-bit patterns using the older `Layer` API. |
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| `test_gaussian_autoencoder.py` | GB-RBM | Auto-encoder on synthetic Gaussian blob images (8×8). Trains, reconstructs, and plots original vs. reconstruction. |
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| `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. |
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| `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. |
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| `test_sub_image.py` | — | Unit test for `SubImage` (patch extraction). No RBM involved. |
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| `test_sub_image.py` | — | Unit test for `SubImage` (patch extraction). No RBM involved. |
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| `test_conv2d.py` | — | Unit test for `conv2d`. No RBM involved. |
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| `test_conv2d.py` | — | Unit test for `conv2d`. No RBM involved. |
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