| Name | Version | Summary | date |
| intelelm |
1.2.0 |
IntelELM: A Python Framework for Intelligent Metaheuristic-based Extreme Learning Machine |
2024-10-09 06:10:03 |
| blenderneuron |
2.1.1 |
Interface for Blender <-> NEURON |
2024-10-08 23:37:12 |
| bluecellulab |
2.6.36 |
Biologically detailed neural network simulations and analysis. |
2024-10-02 07:16:40 |
| pypots |
0.8.1 |
A Python Toolbox for Machine Learning on Partially-Observed Time Series |
2024-09-26 05:57:24 |
| contextual-bandits-algos |
0.1.0 |
A library for contextual multi-armed bandit algorithms. |
2024-09-15 22:36:26 |
| ai4ts |
0.0.3 |
AI for Time Series |
2024-09-14 02:08:54 |
| pytagi |
0.1.11 |
Tractable Approximate Gaussian Inference |
2024-09-13 12:48:41 |
| TimeSeriesAI |
0.0.0 |
AI for Time Series |
2024-09-07 16:53:00 |
| inox |
0.6.3 |
Stainless neural networks in JAX |
2024-09-02 10:25:38 |
| MIDASpy |
1.4.1 |
Multiple Imputation with Denoising Autoencoders |
2024-08-31 18:17:29 |
| MiniSom |
2.3.3 |
Minimalistic implementation of the Self Organizing Maps (SOM) |
2024-08-23 12:22:45 |
| TfELM |
1.1 |
This framework provides a comprehensive set of tools and utilities for implementing and experimenting with Extreme Learning Machines using Python and TensorFlow. ELMs are a type of machine learning algorithm known for their simplicity, efficiency, and scalability, making them ideal for various applications, including classification, regression, and feature learning tasks. |
2024-08-20 09:28:42 |
| xcsf |
1.4.7 |
XCSF learning classifier system: rule-based evolutionary machine learning |
2024-08-19 18:38:12 |
| soft-comp |
0.0.1.dev19 |
Soft-Computing algorithms and helpers for lecture and exercises - Intelligent Embedded Systems (IES), University of Kassel |
2024-08-19 13:13:40 |
| benchpots |
0.2.2 |
A Python Toolbox for Benchmarking Machine Learning on Partially-Observed Time Series |
2024-08-14 17:38:01 |
| AttentionMechanism |
1.0.2 |
This repository contains an implementation of many attention mechanism models. |
2024-08-12 10:27:32 |
| arnet |
0.0.1 |
Nonlinear autoregression with feed-forward neural networks (or any estimator really) |
2024-08-03 11:06:45 |
| dl4d |
1.8.1 |
Deep Learning for empirical DownScaling |
2024-08-01 06:46:47 |
| fastvpinns |
1.0.2 |
A fast tensor-driven variational physics-informed neural network library for solving PDEs. |
2024-07-29 19:09:25 |
| mdgrad |
0.3 |
Tensor-based autdiff engine and neural network API |
2024-07-13 17:55:21 |