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Author SHA1 Message Date
jensandClaude Sonnet 4.6 7bbacc729b [README] - document all bug fixes in implementation notes 
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-05-30 14:47:23 +02:00
jensandClaude Sonnet 4.6 7d48f835a6 [bugfix] - fix momentum reset, cd_gaussian_gaussian noise, rms_error, label CuPy compat 
- train.py: grad_zero() was called inside the epoch loop, resetting momentum
  to zero before every update — momentum had no effect in the default full-batch
  case. Moved outside the loop so momentum accumulates across epochs.
- train.py: cd_gaussian_gaussian: use mean h for weight updates and sampled h
  to drive the negative visible reconstruction (same pattern as cd_gaussian_binary fix).
  Remove spurious Gaussian noise added to data_neg before computing h_probs_neg.
- matrix.py: rms_error divided by d_err_squared[1] (row 1) instead of
  d_err_squared.shape[1] (column count).
- label.py: _dec_binary used reversed() on a CuPy array — replaced with np.flip().
  label2vec_onehot now returns np.stack() array instead of a Python list.
  vec2label_onehot implemented via np.argmax (was returning None).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-05-30 14:46:45 +02:00
jensandClaude Sonnet 4.6 f0e98eb714 [README] - document cd_gaussian_binary bug fixes 
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-05-30 14:37:27 +02:00
jensandClaude Sonnet 4.6 07e430f109 [cd_gaussian_binary] - fix negative phase: remove spurious noise, sample hidden states 
In cd_gaussian_binary, two CD formulation bugs:
1. Gaussian noise was incorrectly added to data_neg before computing h_probs_neg
2. Negative visible reconstruction used h_probs_pos (soft probabilities) instead
   of sampled binary hidden states, biasing the fantasy particle toward the mean

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-05-30 14:36:18 +02:00
jensandClaude Sonnet 4.6 3c85705d85 [README] - add gaussian_autoencoder test entry 
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-05-30 14:29:25 +02:00
jensandClaude Sonnet 4.6 b032db3099 [gaussian_autoencoder] - add GB-RBM autoencoder test with Gaussian blob data 
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-05-30 14:28:57 +02:00
jensandClaude Sonnet 4.6 86d39813cd [binary_autoencoder] - add BB-RBM autoencoder test and tests README 
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-05-30 14:24:49 +02:00
jensandClaude Sonnet 4.6 95be9dd632 [conv2d] - add 2D convolution function and test 
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
 2026-05-29 10:11:11 +02:00
jens 759f4b5348 updated notebooks 2026-01-11 11:23:35 +01:00
jens 92afc16137 [SubImage] 
- handle different image shapes
 2026-01-11 11:21:42 +01:00
jens 3f4cdc277f updated notebooks 2026-01-10 22:19:52 +01:00
jens 51a06605dd [cifar_test_sub_image] 
- use L1-regulation
 2026-01-10 22:18:45 +01:00
jens 7220d41e02 [cifar-test] 
- found good L1-regulation parameter for sparse weights
 2026-01-10 21:44:03 +01:00
jens 432a596092 [mnist-test] 
- found good L1-regulation parameter for sparse weights
 2026-01-10 19:58:39 +01:00
jens be64b0f8ce refactored 2026-01-10 16:46:27 +01:00
jens 1722a68b2a [entity] 
- refactored training parameters for grad_compute()
- added l1-norm
- improved tests
 2026-01-10 15:21:40 +01:00
jens 00fe5fd178 updated notebooks 2026-01-10 14:13:18 +01:00
jens f7e3693f45 - added image module with sub image and normalize 
- improved tests
 2026-01-10 14:12:29 +01:00
jens b6a511e33c improved tests 2026-01-10 10:24:50 +01:00
jens f1aae9b0f1 [train] 
- reset grad at start of epoch
[state]
- init(): set default parameter mu=0
 2026-01-10 10:19:30 +01:00
jens 381ec8d0e3 improved tests 2026-01-09 15:28:53 +01:00
jens 4c939cab8b cd_gaussian_binary: no sampling of training data 2026-01-09 15:28:06 +01:00
jens 074ded1581 improved tests 2026-01-06 21:51:28 +01:00
jens 9025f54434 simplified EntityParams.from_dict 2026-01-06 21:49:35 +01:00
jens e7b287e632 - simplified TrainingParams.from_dict 
- fixed test_rbm
 2026-01-06 21:48:09 +01:00
jens 226453c7ae fixed status indention 2026-01-06 21:06:11 +01:00
jens c879ff583b updated notebooks 2026-01-06 20:21:01 +01:00
jens 186fd423b9 updated notebooks 2026-01-06 20:20:43 +01:00
jens 7d3ab02e26 fixed dividing l2-norm by length of vector 2026-01-06 18:17:45 +01:00
jens 542b8ae9b0 added L2-Regulation 2026-01-06 18:00:26 +01:00
jens ff6254a15d - Status has entity paarmeter 
- train provides entity parameter to Status
 2026-01-06 11:29:47 +01:00
jens 42520e5761 improved tests 2026-01-06 09:44:45 +01:00
jens ec5d259ff7 Entity: added property enable training 2026-01-06 09:44:29 +01:00
jens b1fe7229fa updated cifar_test 2026-01-05 21:46:33 +01:00
jens b6a3779bf9 updated cifar_test and mnist_test 2026-01-05 21:39:22 +01:00
jens 74138b5514 train: swapped epochs and mini-batch loop 2026-01-05 20:53:31 +01:00
jens 562e9e9bda added mnist_test 2026-01-05 19:42:01 +01:00
jens ae6ab9b9b5 updated cifar_test 2026-01-05 19:41:43 +01:00
jens d238d2954e grad_compute(): pre-multiply weight decay with learning rate 2026-01-05 19:40:05 +01:00
jens 10999ec731 updated notebook 2026-01-05 18:08:22 +01:00
jens 2fd55ee69c updated notebook 2026-01-05 14:49:03 +01:00
jens fdf4186d6b significantly improved GB-RBM training 2026-01-05 14:16:34 +01:00
jens 9f72c1f253 - added cifar_test as jupiter lab 
- started torch version of RBM
- enable CUDA in matrix
 2026-01-04 18:30:01 +01:00
jens 73d4486fb7 test_norbs: added mode hidden gaussian - hidden binary 2026-01-04 16:06:41 +01:00
jens 6546c37657 train: fixed gaussian sampling 2026-01-03 19:30:47 +01:00
jens e6c959d890 - fixed test_xor 
- added test_linear
 2026-01-03 13:07:08 +01:00
jens e56f99535a improved tests 2026-01-03 12:51:43 +01:00
jens 529252166a train: sample gaussian visible units 2026-01-03 12:40:08 +01:00
jens 63bfd3ed80 updated 2026-01-03 12:11:04 +01:00
jens f828c26f36 refactored 2026-01-03 12:10:53 +01:00