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.

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

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.