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Adversarial Time-to-Event Modeling
v1v2 (latest)

Adversarial Time-to-Event Modeling

9 April 2018
Paidamoyo Chapfuwa
Chenyang Tao
Chunyuan Li
C. Page
B. Goldstein
Lawrence Carin
Ricardo Henao
    AAMLOODCML
ArXiv (abs)PDFHTML

Papers citing "Adversarial Time-to-Event Modeling"

24 / 24 papers shown
Title
BACE-RUL: A Bi-directional Adversarial Network with Covariate Encoding for Machine Remaining Useful Life Prediction
BACE-RUL: A Bi-directional Adversarial Network with Covariate Encoding for Machine Remaining Useful Life Prediction
Zekai Zhang
Dan Li
Shunyu Wu
Junya Cai
Bo Zhang
See-Kiong Ng
Zibin Zheng
AI4CE
50
0
0
14 Mar 2025
Towards Flexible Time-to-event Modeling: Optimizing Neural Networks via
  Rank Regression
Towards Flexible Time-to-event Modeling: Optimizing Neural Networks via Rank Regression
Hyunjun Lee
Junhyun Lee
Tae-Kil Choi
Jaewoo Kang
Sangbum Choi
OODCML
50
1
0
16 Jul 2023
Explainable Predictive Maintenance
Explainable Predictive Maintenance
Sepideh Pashami
Sławomir Nowaczyk
Yuantao Fan
Jakub Jakubowski
Nuno Paiva
...
Bruno Veloso
M. Sayed-Mouchaweh
L. Rajaoarisoa
Grzegorz J. Nalepa
João Gama
77
9
0
08 Jun 2023
AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis
  on Whole-Slide Images
AdvMIL: Adversarial Multiple Instance Learning for the Survival Analysis on Whole-Slide Images
Pei Liu
Luping Ji
Feng Ye
Bo Fu
76
29
0
13 Dec 2022
Survival Kernets: Scalable and Interpretable Deep Kernel Survival
  Analysis with an Accuracy Guarantee
Survival Kernets: Scalable and Interpretable Deep Kernel Survival Analysis with an Accuracy Guarantee
George H. Chen
471
3
0
21 Jun 2022
auton-survival: an Open-Source Package for Regression, Counterfactual
  Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data
auton-survival: an Open-Source Package for Regression, Counterfactual Estimation, Evaluation and Phenotyping with Censored Time-to-Event Data
Chirag Nagpal
Willa Potosnak
A. Dubrawski
CMLOOD
128
24
0
15 Apr 2022
The Concordance Index decomposition: A measure for a deeper
  understanding of survival prediction models
The Concordance Index decomposition: A measure for a deeper understanding of survival prediction models
Abdallah Alabdallah
Mattias Ohlsson
Sepideh Pashami
Thorsteinn Rögnvaldsson
CML
52
20
0
28 Feb 2022
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event
  Data
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data
Alicia Curth
Changhee Lee
M. Schaar
CML
79
30
0
26 Oct 2021
SurvTRACE: Transformers for Survival Analysis with Competing Events
SurvTRACE: Transformers for Survival Analysis with Competing Events
Zifeng Wang
Jimeng Sun
90
71
0
02 Oct 2021
A Deep Variational Approach to Clustering Survival Data
A Deep Variational Approach to Clustering Survival Data
Laura Manduchi
Ricards Marcinkevics
M. Massi
Thomas Weikert
Alexander Sauter
...
F. Vasella
M. Neidert
M. Pfister
Bram Stieltjes
Julia E. Vogt
146
31
0
10 Jun 2021
Survival Regression with Proper Scoring Rules and Monotonic Neural
  Networks
Survival Regression with Proper Scoring Rules and Monotonic Neural Networks
David Rindt
Robert Hu
D. Steinsaltz
Dino Sejdinovic
191
38
0
26 Mar 2021
Augmenting High-dimensional Nonlinear Optimization with Conditional GANs
Augmenting High-dimensional Nonlinear Optimization with Conditional GANs
P. R. Kalehbasti
M. Lepech
Samarpreet Singh Pandher
GAN
64
3
0
20 Feb 2021
Deep Cox Mixtures for Survival Regression
Deep Cox Mixtures for Survival Regression
Chirag Nagpal
Steve Yadlowsky
Negar Rostamzadeh
Katherine A. Heller
CML
170
62
0
16 Jan 2021
Survival Estimation for Missing not at Random Censoring Indicators based
  on Copula Models
Survival Estimation for Missing not at Random Censoring Indicators based on Copula Models
Mikael Escobar-Bach
Olivier Goudet
31
1
0
03 Sep 2020
SODEN: A Scalable Continuous-Time Survival Model through Ordinary
  Differential Equation Networks
SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks
Weijing Tang
Jiaqi Ma
Qiaozhu Mei
Ji Zhu
86
31
0
19 Aug 2020
Federated Survival Analysis with Discrete-Time Cox Models
Federated Survival Analysis with Discrete-Time Cox Models
M. Andreux
Andre Manoel
Romuald Menuet
C. Saillard
C. Simpson
FedML
102
40
0
16 Jun 2020
Deep Learning for Insider Threat Detection: Review, Challenges and
  Opportunities
Deep Learning for Insider Threat Detection: Review, Challenges and Opportunities
Shuhan Yuan
Xintao Wu
AAML
64
164
0
25 May 2020
Deep Survival Machines: Fully Parametric Survival Regression and
  Representation Learning for Censored Data with Competing Risks
Deep Survival Machines: Fully Parametric Survival Regression and Representation Learning for Censored Data with Competing Risks
Chirag Nagpal
Xinyu Li
A. Dubrawski
OOD
165
123
0
02 Mar 2020
Survival Cluster Analysis
Survival Cluster Analysis
Paidamoyo Chapfuwa
Chunyuan Li
Nikhil Mehta
Lawrence Carin
Ricardo Henao
91
37
0
29 Feb 2020
Survival Function Matching for Calibrated Time-to-Event Predictions
Survival Function Matching for Calibrated Time-to-Event Predictions
Paidamoyo Chapfuwa
Chenyang Tao
Lawrence Carin
Ricardo Henao
OOD
45
4
0
21 May 2019
Time-Series Event Prediction with Evolutionary State Graph
Time-Series Event Prediction with Evolutionary State Graph
Wenjie Hu
Yang Yang
Zilong You
Zongtao Liu
Xiang Ren
AI4TS
45
1
0
10 May 2019
Data-driven Prognostics with Predictive Uncertainty Estimation using
  Ensemble of Deep Ordinal Regression Models
Data-driven Prognostics with Predictive Uncertainty Estimation using Ensemble of Deep Ordinal Regression Models
T. Vishnu
Diksha Garg
Pankaj Malhotra
Lovekesh Vig
Gautam M. Shroff
UQCV
69
16
0
23 Mar 2019
Nonparametric Bayesian Lomax delegate racing for survival analysis with
  competing risks
Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks
Quan Zhang
Mingyuan Zhou
48
17
0
19 Oct 2018
SAFE: A Neural Survival Analysis Model for Fraud Early Detection
SAFE: A Neural Survival Analysis Model for Fraud Early Detection
Panpan Zheng
Shuhan Yuan
Xintao Wu
56
40
0
12 Sep 2018
1