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 calibratio…

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.

Code for: A probabilistic estimation of remaining useful life from censored time-to-event data (2024)

FPBoost: a gradient boosting model for survival analysis that builds hazard functions as a combination of fully parametric hazards.

Code for: Efficient Training of Probabilistic Neural Networks for Survival Analysis (IEEE JBHI 2024)

MENSA: A Multi-Event Network for Survival Analysis under Informative Censoring (2024)

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

MambaOut: Do We Really Need Mamba for Vision?

Implementation of Predicting Survival Time of Ball Bearings in the Presence of Censoring (AAAI Fall Symposium 2023)

Predictive maintenance with survival analysis

PyTorch implementation of DeepWeiSurv, by Bennis, A., Mouysset, S., & Serrurier, M. (2020, May). Estimation of conditional mixture Weibull distribution with right censored data using neural network…

Display dependency tree of Python distribution

Package for easy packaging of Python code

A learning rate range test implementation in PyTorch

SurvSHAP(t): Time-dependent explanations of machine learning survival models

Python library for multivariate dependence modeling with Copulas

Text classification models. Used a submodule for other projects.

A Tensorflow 2.0 implementation of TabNet.

PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf

A simple LaTeX package for formatting responses to journal reviews.

Copula-GP model

A Python library for vine copula models

A Multi-Task Learning Formulation for Survival Analysis

Multi-task survival analysis via regularized Cox regression

DeepHit: A Deep Learning Approach to Survival Analysis with Competing Risks

SurvTRACE: Transformers for Survival Analysis with Competing Events

Unofficial implementation of: Multi-task learning using uncertainty to weigh losses for scene geometry and semantics