Co-occurring keywords · papers mentioning both
Papers
COBALT: Censored Optimization and Bayesian Active Learning Techniques
UAI 2026
Advancing Fairness in Precision Medicine: A Universal Framework for Optimal Treatment Estimation in Censored Data
AISTATS 2025
Heterogeneous Treatment Effect in Time-to-Event Outcomes: Harnessing Censored Data with Recursively Imputed Trees
ICML 2025
Learning High-dimensional Gaussians from Censored Data
AISTATS 2025
Mixed Type Multimorbidity Variational Autoencoder: A Deep Generative Model for Multimorbidity Analysis
MLHC 2024
Toward Conditional Distribution Calibration in Survival Prediction
NeurIPS 2024
An Effective Meaningful Way to Evaluate Survival Models
ICML 2023
Censored Fairness through Awareness
AAAI 2023
Conditional Distribution Function Estimation Using Neural Networks for Censored and Uncensored Data
JMLR 2023
Differentiable sorting for censored time-to-event data.
NeurIPS 2023
Learning Mixtures of Gaussians with Censored Data
ICML 2023
Multi-Source Survival Domain Adaptation
AAAI 2023
Spearman Rank Correlation Screening for Ultrahigh-Dimensional Censored Data
AAAI 2023
A Deep Variational Approach to Clustering Survival Data
ICLR 2022
Censored Quantile Regression Neural Networks for Distribution-Free Survival Analysis
NeurIPS 2022
SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks
JMLR 2022
Survival regression with proper scoring rules and monotonic neural networks
AISTATS 2022
Bayes DistNet - A Robust Neural Network for Algorithm Runtime Distribution Predictions
AAAI 2021
Efficient Algorithms for Learning from Coarse Labels
COLT 2021
T-SCI: A Two-Stage Conformal Inference Algorithm with Guaranteed Coverage for Cox-MLP
ICML 2021
Censored Quantile Regression Forest
AISTATS 2020
Gaussian Sum-Product Networks Learning in the Presence of Interval Censored Data
PGM 2020
Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis
ACML 2020
scikit-survival: A Library for Time-to-Event Analysis Built on Top of scikit-learn
JMLR 2020
A maximum-mean-discrepancy goodness-of-fit test for censored data
AISTATS 2019