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jensandClaude Sonnet 4.6 586803856f [context33] - add batch tiling (N_REPEAT=500) for GPU utilisation 
Tile the single sentence 500× to form a (500, T, 40) batch so matrix ops
are (500, 168) instead of (1, 168). Note: with identical rows the gradient
is mathematically equivalent to batch=1; real speedup requires diverse data.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-31 20:03:03 +02:00
src
[StackRnn] - temporal-shift padding, joint training, vocab reduction, TEMPORAL_DEPTH=64
2026-05-31 14:37:08 +02:00
.gitignore
updated gitignore
2025-12-19 11:11:00 +01:00
cifar_test_sub_image.ipynb
updated notebooks
2026-01-11 11:23:35 +01:00
cifar_test.ipynb
[cifar-test]
2026-01-10 21:44:03 +01:00
context33.ipynb
[context33] - add batch tiling (N_REPEAT=500) for GPU utilisation
2026-05-31 20:03:03 +02:00
layer_test.ipynb
refactored
2025-12-19 15:20:04 +01:00
mnist_test_sub_image.ipynb
updated notebooks
2026-01-11 11:23:35 +01:00
mnist_test.ipynb
[mnist-test]
2026-01-10 19:58:39 +01:00
moby_rnn.ipynb
[StackRnn] - temporal-shift padding, joint training, vocab reduction, TEMPORAL_DEPTH=64
2026-05-31 14:37:08 +02:00
pyproject.toml
added matplotlib
2025-12-18 07:56:45 +01:00
README_moby_rnn.md
[StackRnn] - temporal-shift padding, joint training, vocab reduction, TEMPORAL_DEPTH=64
2026-05-31 14:37:08 +02:00
README.md
added L2-Regulation
2026-01-06 18:00:26 +01:00
test_params.json
added Test passed message
2025-12-16 21:46:00 +01:00

README.md

GRBM

Paper

https://medium.com/@rtdcunha/gaussian-bernoulli-restricted-boltzmann-machines-4a68b8765485 https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0171015&type=printable

Code

https://github.com/DSL-Lab/GRBM/tree/main

CRBM

Paper

https://www.ee.nthu.edu.tw/hchen/pubs/iee2003.pdf

Regularization

https://benihime91.github.io/blog/machinelearning/deeplearning/python3.x/tensorflow2.x/2020/10/08/adamW.html https://medium.com/analytics-vidhya/l1-vs-l2-regularization-which-is-better-d01068e6658c https://jamesmccaffreyblog.com/2019/05/09/the-difference-between-neural-network-l2-regularization-and-weight-decay

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Description
Restricted Boltzmann Machine (RBM) for python
Readme
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Jupyter Notebook 96.9%
Python 3.1%