shi-ang

BNN-ISD

Code Release for "Using Bayesian Neural Networks to Select Features and Compute Credible Intervals for Personalized Survival Prediction"

CensoredMAE

Code Release for "An Effective Meaningful Way to Evaluate Survival Models", ICML 2023

CMPUT566

CMPUT566 UofAlberta

CSD

Conformalized Survival Distribution (CSD) is a plug-in post-processing method designed to enhance the calibration of a survival distribution model, without compromising its discriminative power.

DepressionDetect

ISDEvaluation

Code to pair with the paper "Effective Ways to Build and Evaluate Individual Survival Distributions".

MakeSurvivalCalibratedAgain

This repository contains the code for two conformal prediction-based methods presented at ICML 2024 and NeurIPS 2024. These plug-in post-processing techniques are designed to improve the calibration of survival distribution models while preserving their discriminative power.

SurvivalAnalysisPapers

A list of papers/resources in Survival Analysis that I have read or would like to read.

SurvivalEVAL

The most comprehensive Python package for evaluating survival analysis models.

torchmtlr

Flexible and modular implementation of multi-task logistic regression in PyTorch.

shi-ang/SurvivalAnalysisPapers

A list of papers/resources in Survival Analysis that I have read or would like to read.

shi-ang/SurvivalEVAL

The most comprehensive Python package for evaluating survival analysis models.

shi-ang/MakeSurvivalCalibratedAgain

This repository contains the code for two conformal prediction-based methods presented at ICML 2024 and NeurIPS 2024. These plug-in post-processing techniques are designed to improve the calibration of survival distribution models while preserving their discriminative power.

shi-ang/CensoredMAE

Code Release for "An Effective Meaningful Way to Evaluate Survival Models", ICML 2023

shi-ang/CSD

Conformalized Survival Distribution (CSD) is a plug-in post-processing method designed to enhance the calibration of a survival distribution model, without compromising its discriminative power.

shi-ang/BNN-ISD

Code Release for "Using Bayesian Neural Networks to Select Features and Compute Credible Intervals for Personalized Survival Prediction"

shi-ang/torchmtlr

Flexible and modular implementation of multi-task logistic regression in PyTorch.

shi-ang/DepressionDetect

shi-ang/CMPUT566

CMPUT566 UofAlberta

shi-ang/ISDEvaluation

Code to pair with the paper "Effective Ways to Build and Evaluate Individual Survival Distributions".

shi-ang/Kaggle_Titanic

Intro to Kaggle competition

shi-ang/lifelines

Survival analysis in Python

shi-ang/NN_pytorch

This repository contains code implementation of deep learning algorithm

shi-ang/Shanghuo_Patient_Classifier

The final project of CMPUT 566

shi-ang/shi-ang.github.io

Shi-ang's Personal Website. See https://shi-ang.github.io/

shi-ang/TreeHMM

shi-ang/VAECox

ISMB 2020: Improved survival analysis by learning shared genomic information from pan-cancer data