Popular GitHub Repositories for F Algebras

.NET Standard bindings for Google's TensorFlow for developing, training and deploying Machine Learning models in C# and F#.

TensorFlow API for .NET languages

Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

Awesome Generative Adversarial Networks with tensorflow

Keras.NET is a high-level neural networks API for C# and F#, with Python Binding and capable of running on top of TensorFlow, CNTK, or Theano.

vendor independent TinyML deep learning library, compiler and inference framework microcomputers and micro-controllers

Official repository for the paper F, B, Alpha Matting

Choose your diffusion models and spin up a WebUI on Colab in one click

Search for anything using Google, DuckDuckGo, phind.com, Contains AI models, can transcribe yt videos, temporary email and phone number generation, has TTS support, webai (terminal gpt and open interpreter) and offline LLMs

statistical testing, linear algebra, machine learning, fitting and signal processing in F#

[Not Actively Maintained] Whitebox is an open source E2E ML monitoring platform with edge capabilities that plays nicely with kubernetes

Wayeb is a Complex Event Processing and Forecasting (CEP/F) engine written in Scala.

PyTorch implementation of the Factorized TDNN (TDNN-F) from "Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks" and Kaldi

[ECCV 2020] Official Pytorch implementation for "Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification". SOTA results for ZSL and GZSL

[ICRA2024] Stein Variational Guided Model Predictive Path Integral Control: Proposal and Experiments with Fast Maneuvering Vehicles

[Paper][ISWC 2021] Zero-shot Visual Question Answering using Knowledge Graph

A small open source 3D agent simulator based on LLM.

Frustum-PointPillars: A Multi-Stage Approach for 3D Object Detection using RGB Camera and LiDAR

This clustering based anomaly detection project implements unsupervised clustering algorithms on the NSL-KDD and IDS 2017 datasets

一个 Python 库，用于计算两个输入之间的梅尔倒谱距离（梅尔倒谱失真，MCD）。此实现基于 Robert F. Kubichek 在“用于客观语音质量评估的梅尔倒谱距离度量”中提出的方法。