Propagate and Inject: Revisiting Propagation-Based Feature Imputation for Graphs with Partially Observed Features
No official code found. Best implementation: daehoum1/fisf (0 stars, Apache-2.0, last commit 2025-09-20).
No official code found. Best implementation: daehoum1/fisf (0 stars, Apache-2.0, last commit 2025-09-20).
Reaction Graph: Towards Reaction-Level Modeling for Chemical Reactions with 3D Structures
TIGER: Time-Varying Denoising Model for 3D Point Cloud Generation with Diffusion Process
Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency
Methods with Local Steps and Random Reshuffling for Generally Smooth Non-Convex Federated Optimization
Hypervolume Knowledge Gradient: A Lookahead Approach for Multi-Objective Bayesian Optimization with Partial Information
Balancing Risk and Reward: A Batched-Bandit Strategy for Automated Phased Release
@article{um2026propagate,
title = {Propagate and Inject: Revisiting Propagation-Based Feature Imputation for Graphs with Partially Observed Features},
author = {Daeho Um and Sunoh Kim and Jiwoong Park and Jongin Lim and Seong-Jin Ahn and Seulki Park},
year = {2026},
url = {https://api.semanticscholar.org/CorpusID:455302229df144f72c873b885a9d0454a20642f4},
journal = {ICML 2025 2025}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/455302229df144f72c873b885a9d0454a20642f4)