Popular GitHub Repositories for Frequency

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

List of awesome resources for machine learning-based algorithmic trading

[CVPR 2025?] Identity-Preserving Text-to-Video Generation by Frequency Decomposition

[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis

Self-supervised contrastive learning for time series via time-frequency consistency

PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotation).

Tools for Speech Enhancement integrated with Kaldi

Pitch Estimating Neural Networks (PENN)

HFTFramework utilized for research on " A reinforcement learning approach to improve the performance of the Avellaneda-Stoikov market-making algorithm "

:sound: :boy: :girl:Voice based gender recognition using Mel-frequency cepstrum coefficients (MFCC) and Gaussian mixture models (GMM)

Implementation of "MelNet: A Generative Model for Audio in the Frequency Domain"

Real time monaural source separation base on fully convolutional neural network operates on Time-frequency domain.

Radio Frequency Machine Learning with PyTorch

A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.

A C++ library providing fast language model queries in compressed space.

Implementation of various deep learning models for limit order book. DeepLOB (Zhang et al., 2018), TransLOB (Wallbridge, 2020), DeepFolio (Sangadiev et al., 2020), etc.

【CVPR2024】Magic Tokens: Select Diverse Tokens for Multi-modal Object Re-Identification

Fre-GAN: Adversarial Frequency-consistent Audio Synthesis

[ICLR 2025] CATCH: Channel-Aware Multivariate Time Series Anomaly Detection via Frequency Patching

TFGAN: Time and Frequency Domain Based Generative Adversarial Network for High-fidelity Speech Synthesis