Online-Recurrent-Extreme-Learning-Machine (OR-ELM) for time-series prediction, implemented in python

Extreme Learning Machine implemented in Pytorch

A Python 3 framework for Reservoir Computing with a scikit-learn-compatible API.

A tensorflow implementation of OS-ELM (Online Sequential Extreme Learning Machine)

Machine Learning for Synthetic Aperture Radar Autofocus

Pure implementation of ELM (Extreme Learning Machine) in python (just with numpy)

A Numpy Implementation of Extreme Learning Machine (ELM)

Taking causal inference to the extreme!

A Python Implementation of Kernel Extreme Learning Machine for Ordinal Regression

Pytorch implementation of Extreme Learning Machine

Unsupervised Extreme Learning Machine(ELM) is a non-iterative algorithm used for feature extraction. This method is applied on the IRIS Dataset for non-linear feature extraction and clustering using k-means, Self Organizing Maps(Kohonen Network) and EM Algorithm

(Code) A new workload prediction model using extreme learning machine and enhanced tug of war optimization

A comparison of different classifiers in valence and arousal detection using the DEAP database for EEG

Multi-Objective Optimization of ELM for RUL Prediction

Extreme Learning Machine using RcppArmadillo

Repository for "Inverse Kinematics of Tendon Driven Continuum Robots using Invertible Neural Network" (CompAuto 2022)

IntelELM: A Python Framework for Intelligent Metaheuristic-based Extreme Learning Machine

Implementation of an online sequential extreme learning machine with kernels for nonstationary time series prediction.

Algorithms proposed in the following paper: OLIVEIRA, Gustavo HFMO et al. Time series forecasting in the presence of concept drift: A pso-based approach. In: 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2017. p. 239-246.

An experimental API for Extreme Learning machines Neural Networks made with TensorFlow.