493 Open source projects that are alternatives of or similar to causal-learn

Awesome Neural Logic and Causality: MLN, NLRL, NLM, etc. 因果推断，神经逻辑，强人工智能逻辑推理前沿领域。

This repository contains the dataset and the PyTorch implementations of the models from the paper Recognizing Emotion Cause in Conversations.

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.

[CVPR 2021] Counterfactual VQA: A Cause-Effect Look at Language Bias

Machine learning based causal inference/uplift in Python

Python package for the creation, manipulation, and learning of Causal DAGs

My collection of causal inference algorithms built on top of accessible, simple, out-of-the-box ML methods, aimed at being explainable and useful in the business context

Algorithms for causal inference and the detection of dynamical coupling from time series, and for approximation of the transfer operator and invariant measures.

We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.

Must-read papers and resources related to causal inference and machine (deep) learning

Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"

An Open Source Distributed Time Series Database with high performance, high compression ratio and high usability.

Resampling Tools for Time Series Forecasting with Modeltime

关于domain generalization，domain adaptation，causality，robutness，prompt，optimization，generative model各式各样研究的阅读笔记

Collection of several downsampling methods for time series visualisation purposes.

No description or website provided.

Hands-on training labs for Deep Learning in Time Series course by CERTIFAI

天池“资金流入流出预测——挑战baseline”的解决方案，线上效果143.5

Python implementation of AutoPlait (SIGMOD'14) without smoothing algorithm. NOTE: This repository is for my personal use.

Acquire data with honour and wisdom — using the way of the ninja.

This library was developed for economic analysis in the Brazilian scenario (Investments, micro and macroeconomic indicators)

Classifying time series using feature extraction

Making SLOs with Prometheus manageable, accessible, and easy to use for everyone!

R package for statistical inference using partially observed Markov processes

ES6 module of cubism.js, based on d3v5.

Nonparametric estimators of the average treatment effect with doubly-robust confidence intervals and hypothesis tests

A Python library for machine-learning and feedback loops on streaming data

CNN, RNN, and Bayesian NN classification for ECG time-series (using TensorFlow in Swift and Python)

Applying Common-Sense Reasoning to Multi-Modal Dense Video Captioning and Video Question Answering | Python3 | PyTorch | CNNs | Causality | Reasoning | LSTMs | Transformers | Multi-Head Self Attention | Published in IEEE Winter Conference on Applications of Computer Vision (WACV) 2021

To process a Sentinel-2 time series with MAJA cloud detection and atmospheric correction processor

Open weather data for humans

📑Golang Is Good, Structure Is Bad

DANA: Dimension-Adaptive Neural Architecture (UbiComp'21)( ACM IMWUT)

Imputation of Financial Time Series with Missing Values and/or Outliers

Univariate and multivariate time series forecasting

Download and tidy time series data from the Australian Bureau of Statistics in R

🎓 GSU MPA/MPP course on program evaluation and causal inference

GluonTS Deep Learning with Modeltime

Lightweight header-only matrix library (C++) for numerical optimization and machine learning. Contact me if there is an exciting opportunity.

Periodic time series analysis tools based on information theory

💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatments from observational data using neural networks.

Data abstraction, storage, discovery, and serving system

An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R

A Univariate Time Series Analysis and ARIMA Modeling Package in ANSI C. Updated with SARIMAX and Auto ARIMA.

midasml package is dedicated to run predictive high-dimensional mixed data sampling models

No description or website provided.

About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

A Python Package For System Identification Using NARMAX Models

API for manipulating time series on top of Apache Spark: lagged time values, rolling statistics (mean, avg, sum, count, etc), AS OF joins, downsampling, and interpolation

Poor man's time series functionality for PostgreSQL

fast implementation of singular spectrum transformation (change point detection algorithm)

SUpporting GRaphics with R for ANalysing Time Series

Sequence Modeling with Structured State Spaces

Enables extraction of measurement data from binary files with extension 'raw' used by proprietary software imcFAMOS/imcSTUDIO and facilitates its storage in open source file formats

Python package for automatically constructing features from multiple time series

R Functions implementing UCR Matrix Profile Algorithm

A PyTorch implementation of the Light Temporal Attention Encoder (L-TAE) for satellite image time series. classification

A Python package for causal inference using Synthetic Controls

A new and computationally cheap method to perform human activity recognition using PoseNet and LSTM. Where we use PoseNet for Preprocessing and LSTM for understand the sequence.

A time series database prototype with multiple backends