Taking causal inference to the extreme!

MetroPT-3 Anomaly Detection using Machine Learning and Deep Learning

Extreme Learning Machines Framework with Python and TensorFlow

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

Implementation of paper: Rádli, R., & Czúni, L. (2023). Deep Randomized Networks for Fast Learning

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

In this paper, we propose two novel time-efficient formulations of the Twin Extreme Learning Machine, which only require the solution of systems of linear equations for obtaining the final classifier. In this sense, they can combine the benefits of the Twin Support Vector Machine and standard Extreme Learning Machine in the true sense.

As described in "Towards Full On-Tiny-Device Learning: Guided Search for a Randomly Initialized Neural Network"

Implementation of Learning Vector Quantization (LVQ) and Extreme Learning Machine (ELM) with Iris Dataset

Source code for the Diploma Thesis "Evaluation of Extreme Learning Machine as Channel Equalizer for Color-Shift Keying-Based Visible Light Communication Systems Employed in Underground Mining Scenarios", for the fulfillment of the Electrical Engineer Professional Title at the Universidad de Chile.

Machine Learning for Synthetic Aperture Radar Autofocus

In this project it is used a Machine Learning model based on a method called Extreme Learning, with the employment of L2-regularization. In particular, a comparison was carried out between: (A1) which is a variant of incremental extreme learning machine that is QRIELM and (A2) which is a standard momentum descent approach, applied to the ELM.

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

An easy-to-use independent machine learning library for .net. It offers MLP models (including deep RVFL aka ELM) for common ML tasks as well as Reservoir Computer for efficiently solving ML tasks on time series data.

Extreme Learning Machine using RcppArmadillo

An unofficial python implementation of the discriminative graph regularized Extreme Learning Machine (GELM) proposed by Yong Peng et al., with sklearn compatibility

UAV Flight Analysis and ML-powered Rolling Launch Control System. Written in Python and q/kdb+. Deployed at:

Final Project for Bacherol in Industrial Engineering to UPV, Valencia, Spain.

Extreme Learning Machine for image classification implemented using Cuda C++ and cuBLAS

Exercises and assignments made during a Computational Intelligence class at Federal University Of Ceará.