DNNSurv: Deep Neural Networks for Survival Analysis Using Pseudo Values

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DNNSurv: Deep Neural Networks for Survival Analysis Using Pseudo Values

6 August 2019

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Papers citing "DNNSurv: Deep Neural Networks for Survival Analysis Using Pseudo Values"

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Title
Survival Analysis as Imprecise Classification with Trainable Kernels A. Konstantinov Vlada A. Efremenko Lev V. Utkin 42 0 0 11 Jun 2025
Interpretable Machine Learning for Survival Analysis Sophie Hanna Langbein Mateusz Krzyzinski Mikolaj Spytek Hubert Baniecki P. Biecek Marvin N. Wright 85 2 0 15 Mar 2024
BENK: The Beran Estimator with Neural Kernels for Estimating the Heterogeneous Treatment Effect Stanislav R. Kirpichenko Lev V. Utkin A. Konstantinov CML 106 0 0 19 Nov 2022
Unifying Gradients to Improve Real-world Robustness for Deep Networks Yingwen Wu Sizhe Chen Kun Fang Xiaolin Huang AAML 88 3 0 12 Aug 2022
Fast approximations of pseudo-observations in the context of right-censoring and interval-censoring Olivier Bouaziz 30 0 0 07 Sep 2021
BDNNSurv: Bayesian deep neural networks for survival analysis using pseudo values Dai Feng Lili Zhao 48 32 0 07 Jan 2021
DeepHazard: neural network for time-varying risks Denise Rava Jelena Bradic 52 7 0 26 Jul 2020
A robust algorithm for explaining unreliable machine learning survival models using the Kolmogorov-Smirnov bounds M. Kovalev Lev V. Utkin AAML 81 32 0 05 May 2020
SurvLIME-Inf: A simplified modification of SurvLIME for explanation of machine learning survival models Lev V. Utkin M. Kovalev E. Kasimov 53 10 0 05 May 2020