Popular GitHub Repositories for Feedforward

A 2D Unity simulation in which cars learn to navigate themselves through different courses. The cars are steered by a feedforward neural network. The weights of the network are trained using a modified genetic algorithm.

? A portable, header-only, artificial neural network library written in C99

Unofficial implementation of Google's FNet: Mixing Tokens with Fourier Transforms

ModuleFormer is a MoE-based architecture that includes two different types of experts: stick-breaking attention heads and feedforward experts. We released a collection of ModuleFormer-based Language Models (MoLM) ranging in scale from 4 billion to 8 billion parameters.

Feedforward neural doodle

Minimalistic implementation of a simple feedforward Neural Network

SimpleDNN is a machine learning lightweight open-source library written in Kotlin designed to support relevant neural network architectures in natural language processing tasks

[NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets

Open-source machine learning framework for Java. Designed with speed and lightweight in mind.

[ICLR 2023] MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization

A Deep Learning framework that analyses Windows PE files to detect malicious Softwares.

OmniVCus: Feedforward Subject-driven Video Customization with Multimodal Control Conditions

State of the Art Neural Networks for Deep Learning

Feedforward neural network learning in real time

A deep learning library for use in high-performance computing applications in modern Fortran

Wonderful Matrices to Build Small Language Models

Repository containing the colab-notebooks of the course i did on deep learning from One-Fourth-Labs

Yet another neural network library

This code implements a basic MLP for speech recognition. The MLP is trained with pytorch, while feature extraction, alignments, and decoding are performed with Kaldi. The current implementation supports dropout and batch normalization. An example for phoneme recognition using the standard TIMIT dataset is provided.