FFFinale

ai-economist

Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).

ai-roadmap

ApacheCN AI 路线图（知识树）

annotated_deep_learning_paper_implementations

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

awesome-algorithm

刷题训练指南

awesome-causality-algorithms

An index of algorithms for learning causality with data

awesome-causality-data

A data index for learning causality.

awesome-fairness-in-ai

A curated list of awesome Fairness in AI resources

awesome-fairness-papers

Papers on fairness in NLP

bartpy

Bayesian Additive Regression Trees For Python

causal-network-embeddings

Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"

FFFinale/ai-economist

Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies, as done by the AI Economist (https://www.einstein.ai/the-ai-economist).

FFFinale/annotated_deep_learning_paper_implementations

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

FFFinale/awesome-causality-algorithms

An index of algorithms for learning causality with data

FFFinale/awesome-fairness-in-ai

A curated list of awesome Fairness in AI resources

FFFinale/awesome-fairness-papers

Papers on fairness in NLP

FFFinale/bartpy

Bayesian Additive Regression Trees For Python

FFFinale/causal-network-embeddings

Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"

FFFinale/causallib

A Python package for modular causal inference analysis and model evaluations

FFFinale/CBPS

R package: CBPS

FFFinale/CLUB

Code for ICML2020 paper - CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information

FFFinale/ddz-ai

以孤立语假设和宽度优先搜索为基础，构建了一种多通道堆叠注意力Transformer结构的斗地主ai

FFFinale/DeepFeatureIV

Code for "Learning Deep Features in Instrumental Variable Regression" (https://arxiv.org/abs/2010.07154)

FFFinale/DMLab2020VFAE

Data Mining Lab 2020. The Variational Fair Autoencoder.

FFFinale/eiil

Code for Environment Inference for Invariant Learning (ICML 2020 UDL Workshop Paper)

FFFinale/FedAvg

Implement FedAvg algorithm based on Tensorflow

FFFinale/folktables

Datasets derived from US census data

FFFinale/GraphRec-WWW19

Graph Neural Networks for Social Recommendation, WWW'19

FFFinale/HRM

The code for the paper 'Heterogeneous Risk Minimization' of ICML2021.

FFFinale/InvariantRiskMinimization

PyTorch code to run synthetic experiments.

FFFinale/kernel_proxies

There is where we develop code for the kernel proxy project.

FFFinale/Kernelized-HRM

The code for our NeurIPS 2021 paper "Kernelized Heterogeneous Risk Minimization".

FFFinale/mml-book.github.io

Companion webpage to the book "Mathematics For Machine Learning"

FFFinale/network-deconfounder-wsdm20

Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.

FFFinale/proxy-anchor-regression

FFFinale/PyTorch-VAE

A Collection of Variational Autoencoders (VAE) in PyTorch.

FFFinale/Reinforcement-Learning-2nd-Edition-by-Sutton-Exercise-Solutions

Solutions of Reinforcement Learning, An Introduction

FFFinale/stable-diffusion

A latent text-to-image diffusion model

FFFinale/Tip-Adapter

FFFinale/transferlearning

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

FFFinale/VariationalPrivacyFairness