34 Open source projects that are alternatives of or similar to ACE

Papers, authors and author affiliations from ICML, NeurIPS and ICLR 2006-2021

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

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.

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

Regulatory networks with Direct Information in python

A Causal Relation Schema for Text

Causal Deconvolution of Networks by Algorithmic Generative Models

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

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

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.

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。

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

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

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

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

Machine learning based causal inference/uplift in Python

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

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

Papers with code. Sorted by stars. Updated weekly.

Official Pytorch implementation of ReBias (Learning De-biased Representations with Biased Representations), ICML 2020

Official PyTorch implementation of Time-aware Large Kernel (TaLK) Convolutions (ICML 2020)

This repository contains all the papers accepted in top conference of computer vision, with convenience to search related papers.

ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels

This is a collection of papers and other resources related to fairness.

[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression

Code for the paper Semi-Conditional Normalizing Flows for Semi-Supervised Learning

NeuroAI-UW seminar, a regular weekly seminar for the UW community, organized by NeuroAI Shlizerman Lab.

Code for ICML 2019 paper "Probabilistic Neural-symbolic Models for Interpretable Visual Question Answering" [long-oral]

[ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels

Official code for UnICORNN (ICML 2021)

Implementation of ICML'2021:Neural-Pull: Learning Signed Distance Functions from Point Clouds by Learning to Pull Space onto Surfaces

Code for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)

Complete download for papers in various top conferences

FedScale is a scalable and extensible open-source federated learning (FL) platform.