Proceedings of this symposium are available online at MLR press [http://proceedings.mlr.press/v146/].
Recordings are available for podium presentations only.
Recordings are available for podium presentations only.
Paper ID |
Title |
Authors |
Recordings |
IDNetwork: A deep Illness-Death Network based on multi-states event history process for versatile disease prognostication |
Aziliz Cottin, Nicolas Pécuchet, Marine Zulian,Agathe Guilloux, and Sandrine Katsahian |
||
Beta Survival Models |
David Hubbard, Benoit Rostykus, Yves Raimond and Tony Jebara |
||
Semi-Structured Deep Piecewise Exponential Models |
Philipp Kopper, Sebastian Pölsterl, Christian Wachinger, Bernd Bischl, Andreas Bender and David Rügamer |
||
WRSE - a non-parametric weighted-resolution ensemble for predicting individual survival distributions in the ICU |
Jonathan Heitz, Joanna Ficek, Martin Faltys, Tobias M. Merz, Gunnar Rätsch and Matthias Hüser |
||
Improving the Calibration of Long Term Predictions of Heart Failure Rehospitalizations using Medical Concept Embedding |
Sunil Kalmady, Weijie Sun, Justin Ezekowitz, Nowell Fine, Jonathan Howlett, Anamaria Savu, Russ Greiner and Padma Kaul |
||
Survival Trees for Current Status Data |
Ce Yang, Liqun Diao and Richard Cook |
||
Wavelet Reconstruction Networks for Marked Point Processes |
Jeremy Weiss |
||
The Safe Logrank Test: Error Control under Optional Stopping, Continuation and Prior Misspecification |
Peter Grünwald, Alexander Ly, Muriel Perez-Ortiz and Judith Ter Schure |
||
Empirical Comparison of Continuous and Discrete-time Representations for Survival Prediction |
Michael Sloma, Fayeq Syed, Mohammedreza Nemati and Kevin S. Xu |
||
Transformer-Based Deep Survival Analysis |
Shi Hu, Egill Fridgeirsson, Guido van Wingen and Max Welling |
||
155 |
Theory and software for boosted nonparametric hazard estimation |
Donald Lee, Ningyuan Chen, Hemant Ishwaran, Xiaochen Wang, Arash Pakbin, Bobak Mortazavi and Hongyu Zhao |
|
Dynamic Survival Analysis with Individualized Truncated Parametric Distributions |
Preston Putzel, Padhraic Smyth, Jaehong Yu and Hua Zhong |
||
Harmonic-Mean Cox Models: A Ruler for Equal Attention to Risk |
Xuejian Wang, Wenbin Zhang, Aishwarya Jadhav and Jeremy Weiss |
||
Deep Parametric Time-to-Event Regression with Time-Varying Covariates |
Chirag Nagpal, Vincent Jeanselme and Artur Dubrawski |
||
Exploring the Wasserstein metric for time-to- event analysis |
Tristan Sylvain, Margaux Luck, Joseph Cohen, Heloise Cardinal, Andrea Lodi and Yoshua Bengio |
||
Neural ODEs for Multi-State Survival Analysis |
Stefan Groha, Sebastian Schmon and Alexander Gusev |
||
Survival Prediction Using Deep Learning |
Aliasghar Tarkhan, Noah Simon, Thomas Bengtsson, Kien Nguyen and Jian Dai |
Poster |
|
Risk and Survival Analysis from COVID Outbreak Data : Lessons from India |
Prasad Bankar, Subhasis Panda, Vaibhav Anand and Vineet Kumar |
Poster |
|
133 |
Deep-CR MTLR: a Multi-Modal Approach for Cancer Survival Prediction with Competing Risks |
Sejin Kim, Michal Kazmierski and Benjamin Haibe-Kains |
Poster |
150 Promo Video |
Kullback-Leibler-Based Discrete Relative Risk Models for Integration of Published Prediction Models with New Dataset |
Di Wang, Wen Ye and Kevin He |
Poster |
Finding Relevant Features for Different Times in Survival Prediction by Discrete Hazard Bayesian Network |
Li-Hao Kuan and Russ Greiner |
Poster |
|
Multi-ethnic Survival Analysis: Transfer Learning with Cox Neural Networks |
Yan Gao and Yan Cui |
Poster |
