| Name | Version | Summary | date |
| deepview-predict |
0.1.6.5 |
Cross-GPU performance predictions for PyTorch neural network training. |
2024-12-16 20:38:36 |
| norse |
1.1.0 |
A library for deep learning with spiking neural networks |
2024-03-18 22:39:51 |
| conveiro |
0.2.1 |
Visualization of filters in convolutional neural networks |
2024-03-18 10:14:25 |
| FeaSel-Net |
0.0.10 |
A Keras callback package for recursively pruning the most uninformative input nodes during training. |
2024-03-13 12:28:37 |
| pclib |
2.0.0b2 |
A torch-like package for building Predictive Coding Neural Networks. |
2024-03-06 11:29:50 |
| pyhealth |
1.1.6 |
A Python library for healthcare AI |
2024-02-24 21:18:34 |
| pygod |
1.1.0 |
A Python Library for Graph Outlier Detection (Anomaly Detection) |
2024-02-04 21:25:17 |
| clika-inference |
0.0.2 |
A fake package to warn the user they are not installing the correct package. |
2024-01-31 06:43:35 |
| clika-compression |
0.0.2 |
A fake package to warn the user they are not installing the correct package. |
2024-01-31 06:43:33 |
| clika-client |
0.0.2 |
A fake package to warn the user they are not installing the correct package. |
2024-01-31 06:43:31 |
| clika-ace |
0.0.2 |
A fake package to warn the user they are not installing the correct package. |
2024-01-31 06:43:30 |
| pyEasyML |
2.0.8 |
A python machine learning framework. |
2024-01-10 07:46:53 |
| mitdeeplearning |
0.6.1 |
Official software labs for MIT Introduction to Deep Learning (http://introtodeeplearning.com) |
2024-01-08 06:08:52 |
| vispunk-motion |
0.1.23 |
Vispunk. |
2024-01-03 03:36:16 |
| dropgrad-dingo-actual |
0.1.0 |
A PyTorch implementation of DropGrad regularization. |
2023-12-16 10:59:56 |
| dropgrad |
0.1.0 |
A PyTorch implementation of DropGrad regularization. |
2023-12-16 10:59:55 |
| NNVisualiser |
1.0.0 |
A Neural Network Visualiser as a Python package utilizing Matplotlib, visualizes plot coordinates from NeuralNetworkCoordinates for single-input, single-output neural networks. Aligned with Explainable AI, it offers concise insights, catering to researchers focused on understanding specific network architectures. |
2023-12-06 17:26:10 |
| auto-verify |
0.1.3 |
Efficient portfolio-based verification of neural network properties |
2023-12-06 14:25:00 |
| NeuralNetworkCoordinates |
1.0.0 |
NeuralNetworkCoordinates: Precise coordinates for visualizing intricate neural network transformations. Uncover spatial insights, enhance interpretability, and tailor custom visualizations with this specialized Python package. |
2023-12-06 08:28:01 |
| r2ntab |
1.0.3 |
Interpretable machine learning model for binary classification combining deep learning and rule learning |
2023-12-01 15:16:43 |