Survival Permanental Processes for Survival Analysis with Time-Varying Covariates

Hideaki Kim
2/12/2026

No official code found. Best implementation: HidKim/SurvPP (3 stars, last commit 2023-11-15).

DOISemantic Scholar

Code Implementations(1)

HidKim/SurvPPCommunity64%

Code for "Survival Permanental Processes for Survival Analysis with Time-Varying Covariates" at NeurIPS2023

30PythonOct 5, 20232 years ago
gaussian-processeskernel-methodsneurips-2023point-processessurvival-analysis

Similar Papers

A High-Resolution Dataset for Instance Detection with Multi-View Object Capture

99% match2026

Conformal Prediction for Uncertainty-Aware Planning with Diffusion Dynamics Model

99% match1 repo202026

A Non-Contrastive Learning Framework for Sequential Recommendation with Preference-Preserving Profile Generation

99% match2026

Learning Pseudo 3D Guidance for View-Consistent Texturing with 2D Diffusion

99% match2026

Adaptive Barrier Smoothing for First-Order Policy Gradient with Contact Dynamics

99% match2026

Flow Matching for Few-Trial Neural Adaptation with Stable Latent Dynamics

99% match1 repo42026

Cite this paper

@article{kim2026survival,
  title  = {Survival Permanental Processes for Survival Analysis with Time-Varying Covariates},
  author = {Hideaki Kim},
  year   = {2026},
  doi    = {10.52202/075280-3182},
  url    = {https://doi.org/10.52202/075280-3182},
  journal = {NEURIPS 2023 2023}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/38e708bc0c908e31a120164143739ad9337853c2.svg)](https://codeofpaper.com/paper/38e708bc0c908e31a120164143739ad9337853c2)

Discussion