236 Open source projects that are alternatives of or similar to Causal_Reading_Group

Machine learning based causal inference/uplift in Python

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

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

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

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。

Causal Discovery for Python. Translation and extension of the Tetrad Java code.

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.

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

DEPRECATED This is the official repository for the 2017 Recommender Systems course at Polimi.

PyTorch(1.6+) implementation of https://github.com/kang205/SASRec

🛍️RetailBox - eCommerce Recommender System using Machine Learning

WWW'2019: Modeling Item-Specific Temporal Dynamics of Repeat Consumption for Recommender Systems

Fast item-to-item recommendations on the command line.

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

Causal Inference: What If. R and Stata code for Exercises

🏷️ An e-commerce marketplace template. An online auction and shopping website for buying and selling a wide variety of goods and services worldwide.

Causal Inference for the Brave and True的中文翻译版。全部代码基于Python，适用于计量经济学、量化社会学、策略评估等领域。英文版原作者：Matheus Facure

Recommend system learning resources and learning notes

Search/Recommendation engine and metainformation server for fanfiction net

Knowledge-aware recommendation papers.

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

Policy learning via doubly robust empirical welfare maximization over trees

➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.

FINN.no Slate Dataset for Recommender Systems. A dataset containing all interactions (viewed items + response (clicked item / no click) for users over a longer time horizon.

This is our implementation of SAMN: Social Attentional Memory Network

CausalNLP is a practical toolkit for causal inference with text as treatment, outcome, or "controlled-for" variable.

Fashion Shop App : Flask, ChatterBot, ElasticSearch, Recommender-System

Tf-Rec is a python💻 package for building⚒ Recommender Systems. It is built on top of Keras and Tensorflow 2 to utilize GPU Acceleration during training.

Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)

Mengting Wan, Julian McAuley, "Item Recommendation on Monotonic Behavior Chains", in Proc. of 2018 ACM Conference on Recommender Systems (RecSys'18), Vancouver, Canada, Oct. 2018.

Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893

Visual Similarity research at Fynd. Contains code to reproduce 2 of our research papers.

It is a content based recommender system that uses tf-idf and cosine similarity for N Most SImilar Items from a dataset

RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems

An index of recommendation algorithms that are based on Graph Neural Networks.

Library for graphical models of decision making, based on pgmpy and networkx

MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems, KDD2021

PyTorch implementations of Top-N recommendation, collaborative filtering recommenders.

Factorization Machine, Deep Learning, Recommender System

The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show another successful application of AML in generative adversarial networks (GANs) for generative applications, thanks to their ability for learning (high-…

Summary of social recommendation papers and codes

A Python package for causal inference using Synthetic Controls

QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)

This is our implementation of EATNN: Efficient Adaptive Transfer Neural Network (SIGIR 2019)

This is our implementation of NARRE:Neural Attentional Regression with Review-level Explanations

recommender system tutorial with Python

tf-recsys contains collaborative filtering (CF) model based on famous SVD and SVD++ algorithm. Both of them are implemented by tensorflow in order to utilize GPU acceleration.

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

[ WSDM '19 ] Sequential Variational Autoencoders for Collaborative Filtering

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

Implementing Content based and Collaborative filtering(with KNN, Matrix Factorization and Neural Networks) in Python

A system that will help in a personalized recommendation of courses for an upcoming semester based on the performance of previous semesters.

Building recommender systems in Julia

PyTorch Implementation for Neural Graph Collaborative Filtering

🎯 📕 Targeted Learning in R: A Causal Data Science Handbook

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

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

Recommendation based on sequence

Code for our paper, Neural Network Attributions: A Causal Perspective (ICML 2019).

Built on data from Pluralsight's course API fetched results. Works with model trained with K-means unsupervised clustering algorithm.