Statistical Machine Intelligence & Learning Engine

PyWavelets - Wavelet Transforms in Python

Pytorch implementation of 2D Discrete Wavelet (DWT) and Dual Tree Complex Wavelet Transforms (DTCWT) and a DTCWT based ScatterNet

Wavelet scattering transforms in Python with GPU acceleration

A quick rundown on each feature and its settings

Synchrosqueezing, wavelet transforms, and time-frequency analysis in Python

Progressive, error tolerant, wavelet-based image compression algorithm

A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019)

Wavelet Convolutions for Large Receptive Fields. ECCV 2024.

Fast, efficient and accurate multi-resolution, multi-sensor 3D occupancy mapping

The fast Continuous Wavelet Transform (fCWT) is a library for fast calculation of CWT.

Official Pytorch Implementation of the paper: Wavelet Diffusion Models are fast and scalable Image Generators (CVPR'23)

C Implementation of 1D and 2D Wavelet Transforms (DWT,SWT and MODWT) along with 1D Wavelet packet Transform and 1D Continuous Wavelet Transform.

[JMLR] Differentiable fast wavelet transforms in PyTorch with GPU support.

The fast Continuous Wavelet Transform (fCWT) is a library for fast calculation of CWT.

A Python module for continuous wavelet spectral analysis. It includes a collection of routines for wavelet transform and statistical analysis via FFT algorithm. In addition, the module also includes cross-wavelet transforms, wavelet coherence tests and sample scripts.

PyTorch implementation of the wavelet analysis from Torrence & Compo (1998)

CBF,CVT,DTCWT,GTF,LP,MSVD,RP,Wavelet,CNN,Deepfuse,DenseFuse,FusionGAN,IFCNN,MDlatLRR,DDcGAN,ResNetFusion,NestFuse,NVCE,FusionDN,HybridMSD,PMGI,IFEVIP,StructAware,U2Fusion,MEF-GAN，JSR,ConvSR,DCHWT,MEFGAN,MWFG,PMGI,PANGAN,ect

Python implementation of the wavelet analysis found in Torrence and Compo (1998)

Official pytorch implementation for "Low-light Image Enhancement with Wavelet-based Diffusion Models"

Multi-level Wavelet Convolutional Neural Networks

Torrence & Compo Wavelet Analysis Software

The GoPro® CineForm video codec SDK.

This tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.

Write once, run forever. Deploy robust, scalable, decentralized WebAssembly applications on Wavelet.

This is an official implementation of "SWIFT: State-space Wavelet Integrated Forecasting Technology for Enhanced Time Series Prediction".

A pytorch implementation of Paper "Wavelet-srnet: A wavelet-based cnn for multi-scale face super resolution"

Multi-level Wavelet-CNN for Image Restoration

[CVPR 2021] Monocular depth estimation using wavelets for efficiency

A Discrete Fourier Transform (DFT), a Fast Wavelet Transform (FWT), and a Wavelet Packet Transform (WPT) algorithm in 1-D, 2-D, and 3-D using normalized orthogonal (orthonormal) Haar, Coiflet, Daubechie, Legendre and normalized biorthognal wavelets in Java.