HuShifang's Stars
HumanSignal/labelImg
LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.
wkentaro/labelme
Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).
kornia/kornia
🐍 Geometric Computer Vision Library for Spatial AI
satellite-image-deep-learning/techniques
Techniques for deep learning with satellite & aerial imagery
sktime/sktime
A unified framework for machine learning with time series
py-why/dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
mosaicml/composer
Supercharge Your Model Training
uber/causalml
Uplift modeling and causal inference with machine learning algorithms
Nixtla/statsforecast
Lightning ⚡️ fast forecasting with statistical and econometric models.
py-why/EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
rguo12/awesome-causality-algorithms
An index of algorithms for learning causality with data
tslearn-team/tslearn
The machine learning toolkit for time series analysis in Python
rasterio/rasterio
Rasterio reads and writes geospatial raster datasets
elixir-nx/axon
Nx-powered Neural Networks
patrick-kidger/diffrax
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
JuliaPy/PythonCall.jl
Python and Julia in harmony.
lucidrains/memorizing-transformers-pytorch
Implementation of Memorizing Transformers (ICLR 2022), attention net augmented with indexing and retrieval of memories using approximate nearest neighbors, in Pytorch
BayesianModelingandComputationInPython/BookCode_Edition1
rguo12/awesome-causality-data
A data index for learning causality.
bayesflow-org/bayesflow
A Python library for amortized Bayesian workflows using generative neural networks.
stan-dev/pystan
PyStan, a Python interface to Stan, a platform for statistical modeling. Documentation: https://pystan.readthedocs.io
fcakyon/yolov5-pip
Packaged version of ultralytics/yolov5 + many extra features
lightning-uq-box/lightning-uq-box
Lightning-UQ-Box: Uncertainty Quantification for Neural Networks with PyTorch and Lightning
google/bayesnf
Bayesian Neural Field models for prediction in large-scale spatiotemporal datasets
mikeckennedy/pyscript-pwa-example
DynamicsAndNeuralSystems/pycatch22
python implementation of catch22
Gattocrucco/bartz
Super-fast BART (Bayesian Additive Regression Trees) in Python
baraline/convst
Implementation of the Random Dilated Shapelet Transform algorithm along with interpretability tools. ReadTheDocs documentation is not up to date with the current version for now.
Actis92/lit-saint
nmonnet/Warp-Factory-for-Python
This code explores the computation of the stress-energy tensor for a given spacetime metric, aiming to replicate the functionality of the "Warp Factory" code (arXiv:2404.03095). Unlike that study, this approach uses SymPy and EinsteinPy to derive analytical expressions for key quantities, minimizing reliance on numerical approximations.