Reverse Dependencies of cupy

The following projects have a declared dependency on cupy:

• abTEM — no summary
• acutils-python — Data processing library implemented by Acuzle.
• AKFDTD — Finite difference time domain simulation (for slit diffraction)
• anndata — Annotated data.
• array-api-compat — A wrapper around NumPy and other array libraries to make them compatible with the Array API standard
• artis-tomo — Scientific Methods for tomography
• astro-seeing — Sympy Expressions Evaluation Implemented oN the GPU
• awkward-cuda-kernels — CUDA plug-in for Awkward Array, enables GPU-bound arrays and operations.
• awkward1-cuda-kernels — CUDA plug-in for Awkward Array, enables GPU-bound arrays and operations.
• bayesbridge — Generates posterior samples under Bayesian sparse regression based on the bridge prior using the CG-accelerated Gibbs sampler of Nishimura et. al. (2018). The linear and logistic model are currently supported.
• BioPII — BioPII (Biology Parallel Integral Image) is a Python package for performing sliding window analysis (SWA) on biological images.
• bnpm — A library of useful modules for data analysis.
• bodge — Bodge: Python package for efficient tight-binding modeling of superconductors.
• boid-py — A package for calculating positons of boids
• bucky-covid — The Bucky model is a spatial SEIR model for simulating COVID-19 at the county level.
• CalSciPy — A toolbox for analyzing, designing, and visualizing multiphoton imaging & optogenetics experiments.
• cbmos — A framework for numerical analysis of center-based cell models
• ccpi_regularisation_cupy — GPU-CuPy accelerated regularisation routines of CCPi-regularisation toolkit
• cdsaxs — package streamlines CD-SAXS data analysis by combining model generation, optimization, and uncertainty estimation for nanostructure characterization
• codex-africanus — Radio Astronomy Building Blocks
• congrad — Generic conjugate gradient solver that works with your favorite backend
• cryoCOFI — CarbOn FIlm detector for cryo-EM images
• cryosieve — CryoSieve: a particle sorting and sieving algorithm for single particle analysis in cryo-EM
• cryotrans — CryoTRANS: Predicting high-resolution maps of rare conformations using neural ODEs in cryo-EM
• cupy-knn — A fast nearest neighbor index cuda implementation for 3D points using a lightweight BVH-tree.
• cupy-xarray — Interface for using cupy in xarray, providing convenience accessors.
• cutci — Cutci is a library to calculate Human Thermal Comfort Index (UTCI) by GPU-accelerated computing with CuPy.
• cycoda — no summary
• dask-image — Distributed image processing
• deepnp — Building deep learning models with numpy only
• detectorcal — Ring artefact suppression in X-ray CT using pixel-wise linear correction
• dexp — Light-sheet Dataset EXploration and Processing
• e2eml — An end-to-end solution for automl
• earthstat — EarthStat Library
• EasyIsing — A small package that provides a simple Ising model simulation on a squared lattice with the Metropolis algorithm.
• ebcc — Coupled cluster calculations on electron-boson systems
• emgdecomp — Package for decomposing EMG signals into motor unit firings.
• fast-diff-py — Multiprocessing implementation of difpy with a focus on performance, disk cache and progress retention.
• finch-genetics — A flexible framework for evolutionary algorithms in Python
• franken — Franken fine-tuning scheme for ML potentials
• fridom — Framework for Idealized Ocean Models
• geb — GEB simulates the environment, the individual behaviour of people, households and organizations - including their interactions - at small and large scale.
• gene-scoring — Gene set scoring package for single-cell RNA sequencing data with GPU acceleration.
• gpu-slic — CUDA implementation of the SLIC segmentaion algorithm.
• gpumap — UMAP with GPUs
• gt4py — Python library for generating high-performance implementations of stencil kernels for weather and climate modeling from a domain-specific language (DSL)
• gwpopulation — Unified population inference
• hepaccelerate — Fast kernels for analyzing jagged columnar data common in high-energy physics.
• himalaya — Multiple-target machine learning
• httomo-backends — Supplementary files for HTTomo backends.
• httomolibgpu — Commonly used tomography data processing methods at DLS.
• hypernets — An General Automated Machine Learning Framework
• japanAirAnalytics — This software is being developed at the University of Aizu, Aizu-Wakamatsu, Fukushima, Japan
• jess — Just in Time Elimination of Spurious Signals - jess
• jitfields — Fast utilities for dense scalar and vector fields
• klongpy — High-Performance Klong array language with rich Python integration.
• kltpicker2 — KLT Picker: Particle picking using data-driven optimal templates
• lbmpy — Code Generation for Lattice Boltzmann Methods
• libertem — Open pixelated STEM framework
• locan — Analysis software for single-molecule localization microscopy
• locate-pixelcolor-cupy — Detects colors in images up to 8 times as fast as NumPy
• longitudinal-tomography — A python library for longitudinal particle beam tomography
• mastsel — Asterism Selection for MAVIS instrument
• matvis — Fast matrix-based visibility simulator with interface to CPU and GPU
• Mits-AI-Dreamers — This is Hamming distance, Jaccard coefficient, overlap
• ms-entropy — This package provides a Python implementation of calculating spectral entropy, entropy similarity, and Flash entropy search for mass spectrometry data.
• multinterp — Multivariate Interpolation.
• myylearn — An General Automated Machine Learning Framework
• napari-cupy-image-processing — GPU-accelerated image processing using CUDA
• nettracer3d — Scripts for intializing and analyzing networks from segmentations of three dimensional images.
• nonconvexAG-GPU — (GPU version) Implementation of accelerated gradient algorithm with strong rules for (high-dimensional) nonconvex sparse learning problems.
• NonParametricDensity — Python module for nonparametric density estimation with GPU support.
• okrolearn — A machine learning library created by Okerew, which is supposed to be a raw implementation of combining pytorch with scikit-learn
• openchatkit — OpenChatKit - a powerful, open-source base to create both specialized and general purpose chatbots
• pami — This software is being developed at the University of Aizu, Aizu-Wakamatsu, Fukushima, Japan
• photon-canon — An in-depth 3D Monte Carlo simulation toolbox with custom systems of planar mediums, custom beams and detectors.
• postpruner — no summary
• py4DSTEM — An open source python package for processing and analysis of 4D STEM data.
• pydeepflow — A deep learning package optimized for performing Deep Learning Tasks, easy to learn and integrate into projects
• PyHyperScattering — Utilities for loading, reducing, fitting, and plotting hyperspectral x-ray and neutron scattering data.
• pyLowOrder — High-performance low-order modeling with Python
• pymindcorecupy — A Python library for AI, easy to use, freely available for any use
• pyNeuroTrace — Python code for neural time series
• pyolaf — 3D reconstruction framework for light field microscopy
• pystencils — Speeding up stencil computations on CPUs and GPUs
• pytom-match-pick — PyTOM's GPU template matching module as an independent package
• pywavelet — WDM wavelet transform your time/freq series!
• pyxem — multi-dimensional diffraction microscopy
• raccoon-cluster — Scale-adaptive clustering in Python
• s1280247-learn2 — This ssoftware is being developd in the Python Class, University of Aizu.
• s1282003-learn — This software is being developed at the University of Aizu, Aizu-Wakamatsu, Fukushima, Japan
• s1282006-learn — This software is being developed at the University of Aizu, Aizu-Wakamatsu, Fukushima, Japan
• s1290166-learn — This software is being developed by Hiroyuki Matushima
• s1290229-learn — This software is being developed at the University of Aizu, Aizu-Wakamatsu, Fukushima, Japan
• s1290242-learn — This software is being developed at the University of Aizu, Aizu-Wakamatsu, Fukushima, Japan
• s1292013-learn — This software is being developed at the University of Aizu, Aizu-Wakamatsu, Fukushima, Japan
• s1300180-learn — This software was made for my class
• s1300257-learn — This software is being developed at the University of Aizu, Aizu-Wakamatsu, Fukushima, Japan
• s1300259-learn — This software is being developed at the University of Aizu, Aizu-Wakamatsu, Fukushima, Japan
• scatcluster — A workflow for clustering continuous time series with a deep scattering network.