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adversarial-balancing-based-representation-learning-for-causal-effect-inference

Causal Inference

ai-job-resume

AI 算法岗简历模板

analytics_vidhya

Codes related to activities on AV including articles, hackathons and discussions.

anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

apex

A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

attentionmechanismstrajectoryprediction

In this repository, one can find the code for my master's thesis project. The main goal of the project was to study and improve attention mechanisms for trajectory prediction of moving agents.

avalanche

Avalanche: an End-to-End Library for Continual Learning based on PyTorch.

awesome-causality-algorithms

An index of algorithms for learning causality with data

awesome-causality-data

A data index for learning causality.

benchmarks

bioinfo_pi_atlas

生物信息学方向导师介绍

camelot-icml

Code for submission Learning of Cluster-based Feature Importance for Electronic Health Record Time-series

cevae

Causal Effect Inference with Deep Latent-Variable Models

chinese-std-gb-t-7714-related-csl

GB/T 7714相关的csl以及Zotero使用技巧及教程。

clops

Code to conduct experiments introduced in CLOPS: Continual Learning for Physiological Signals (https://arxiv.org/abs/2004.09578)

cox-nnet

cyclegan

Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.

deep-learning-book-chapter-summaries

Attempting to make the Deep Learning Book easier to understand.

deep-q-networks

Implementations of algorithms from the Q-learning family. Implementations inlcude: DQN, DDQN, Dueling DQN, PER+DQN, Noisy DQN, C51

deeplearningsurvival

PyTorch implementation of Deep Survival Models.

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.

drnet

💉📈 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.

drsa

Deep Recurrent Survival Analysis, an auto-regressive deep model for time-to-event data analysis with censorship handling. An implementation of our AAAI 2019 paper.

fall-detection

Human Fall Detection from CCTV camera feed

gam

A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

gow

Unix command line utilities installer for Windows.

hexo-matery-modified

My personal modified hexo matery theme with some bugs fixed.

hsuantienlin_machinelearning

improving-sepsis-treatment-strategies

This is the repository for paper "Improving Sepsis Treatment Strategies using Deep Reinforcement Learning and Mixture-of-Experts"

lifelines

Survival analysis in Python