NeurIPS 2025 Workshop NPGML Submissions

Temporal Graph AutoEncoder: Mapping Dynamic Graphs to Dynamical Systems with Neural ODEs
Raphael Romero, Rembert Daems, Tijl De Bie
- Published: 23 Sept 2025, Last Modified: 21 Oct 2025
- NPGML Poster
- Readers: Everyone
Connected Causal Graphs for Real-World Science
Amine M'Charrak, Abbavaram Gowtham Reddy, Thomas Lukasiewicz, Michael M. Bronstein, Krikamol Muandet
- Published: 23 Sept 2025, Last Modified: 27 Oct 2025
- NPGML Poster
- Readers: Everyone
Graph Guided Diffusion: Unified Guidance for Conditional Graph Generation
Victor M. Tenorio, Nicolas Zilberstein, Santiago Segarra, Antonio G. Marques
- Published: 23 Sept 2025, Last Modified: 21 Oct 2025
- NPGML Poster
- Readers: Everyone
The Cartesian Gaussian Additive Noise Model for Causal Inference with Dependent Samples
Bailey Andrew, David Robert Westhead, Luisa Cutillo
- Published: 23 Sept 2025, Last Modified: 26 Oct 2025
- NPGML Poster
- Readers: Everyone
Ground-Truth Subgraphs for Better Training and Evaluation of Knowledge Graph Augmented LLMs
Alberto Cattaneo, Carlo Luschi, Daniel Justus
- Published: 23 Sept 2025, Last Modified: 26 Oct 2025
- NPGML Poster
- Readers: Everyone
Equivariant Geometric Scattering Networks via Vector Diffusion Wavelets
David R Johnson, Rishabh Anand, Smita Krishnaswamy, Michael Perlmutter
- Published: 23 Sept 2025, Last Modified: 22 Oct 2025
- NPGML Poster
- Readers: Everyone
Landmark-Based Node Representations for Shortest Path Distance Approximations in Random Graphs
My Le, Luana Ruiz, Souvik Dhara
- Published: 23 Sept 2025, Last Modified: 21 Oct 2025
- NPGML Poster
- Readers: Everyone
Exploring Heterophily in Graph-level Tasks
Qinhan Hou, Yilun Zheng, Xichun Zhang, Sitao Luan, Jing Tang
- Published: 23 Sept 2025, Last Modified: 27 Oct 2025
- NPGML Poster
- Readers: Everyone
A New Perspective for Graph Learning Architecture Design: Linearize Your Depth Away
Joël Mathys, Roger Wattenhofer
- Published: 23 Sept 2025, Last Modified: 27 Oct 2025
- NPGML Poster
- Readers: Everyone
LOBSTUR: A Local Bootstrap Framework for Tuning Unsupervised Representations in Graph Neural Networks
Sowon Jeong, Claire Donnat
- Published: 23 Sept 2025, Last Modified: 21 Oct 2025
- NPGML Poster
- Readers: Everyone
Posterior Label Smoothing for Node Classification
Jaeseung Heo, MoonJeong Park, Dongwoo Kim
- Published: 23 Sept 2025, Last Modified: 21 Oct 2025
- NPGML Poster
- Readers: Everyone
Understanding Generalization in Node and Link Prediction
Antonis Vasileiou, Timo Stoll, Christopher Morris
- Published: 23 Sept 2025, Last Modified: 21 Oct 2025
- NPGML Poster
- Readers: Everyone
FedGraph: A Research Library and Benchmark for Federated Graph Learning
Yuhang Yao, Yuan Li, Xinyi Fan, Junhao Li, Kay Liu, Yu Yang, Weizhao Jin, Srivatsan Ravi, Philip S. Yu, Carlee Joe-Wong
- Published: 23 Sept 2025, Last Modified: 27 Oct 2025
- NPGML Poster
- Readers: Everyone
Overcoming Class Imbalance: Unified GNN Learning with Structural and Semantic Connectivity Representations
Abdullah Alchihabi, Hao Yan, Yuhong Guo
- Published: 23 Sept 2025, Last Modified: 21 Oct 2025
- NPGML Poster
- Readers: Everyone
Topological Clustering of Aphasic Brain Networks
Jiaying Yi, Jian Yin, Rahul Ghosal, Dirk B. den Ouden, Julius Fridriksson, Rutvik Desai, Yuan Wang
- Published: 23 Sept 2025, Last Modified: 24 Oct 2025
- NPGML Poster
- Readers: Everyone
Bridging the Divide: End-to-End Sequence–Graph Learning
Yuen Chen, Yulun Wu, Samuel Sharpe, Igor Melnyk, Nam H Nguyen, Furong Huang, C. Bayan Bruss, Rizal Fathony
- Published: 23 Sept 2025, Last Modified: 27 Oct 2025
- NPGML Poster
- Readers: Everyone
Generalizable Insights for Graph Transformers in Theory and Practice
Timo Stoll, Luis Müller, Christopher Morris
- Published: 23 Sept 2025, Last Modified: 27 Oct 2025
- NPGML Poster
- Readers: Everyone
Deep Modularity Networks with Diversity-Preserving Regularization
Yasmin Salehi, Dennis Giannacopoulos
- Published: 23 Sept 2025, Last Modified: 27 Oct 2025
- NPGML Poster
- Readers: Everyone
Learning the Neighborhood: Contrast-Free Self-Supervised Molecular Graph Pretraining
Boshra Ariguib, Mathias Niepert, Andrei Manolache
- Published: 23 Sept 2025, Last Modified: 26 Oct 2025
- NPGML Poster
- Readers: Everyone
Learning (Approximately) Equivariant Networks via Constrained Optimization
Andrei Manolache, Luiz F. O. Chamon, Mathias Niepert
- Published: 23 Sept 2025, Last Modified: 21 Oct 2025
- NPGML Poster
- Readers: Everyone
Predicting Microbial Interactions Using Graph Neural Networks
Elham Gholamzadeh, Kajal Singla, Nico Scherf
- Published: 23 Sept 2025, Last Modified: 21 Oct 2025
- NPGML Poster
- Readers: Everyone
Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement
Huidong Liang, Haitz Sáez de Ocáriz Borde, Baskaran Sripathmanathan, Michael M. Bronstein, Xiaowen Dong
- Published: 23 Sept 2025, Last Modified: 21 Oct 2025
- NPGML Poster
- Readers: Everyone
Long-Range Graph Wavelet Networks
Filippo Guerranti, Fabrizio Forte, Simon Geisler, Stephan Günnemann
- Published: 23 Sept 2025, Last Modified: 24 Oct 2025
- NPGML Poster
- Readers: Everyone
Self-Exploring Language Models for Explainable Link Forecasting on Temporal Graphs via Reinforcement Learning
Zifeng Ding, Shenyang Huang, Zeyu Cao, Emma Kondrup, Zachary Yang, Xingyue Huang, Yuan Sui, Moy Yuan, Yuqicheng Zhu, Xianglong Hu, Yuan He, Farimah Poursafaei, Michael M. Bronstein, Andreas Vlachos
- Published: 23 Sept 2025, Last Modified: 25 Oct 2025
- NPGML Poster
- Readers: Everyone
Efficient Learning on Large Graphs using a Densifying Regularity Lemma
Jonathan Kouchly, Ben Finkelshtein, Michael M. Bronstein, Ron Levie
- Published: 23 Sept 2025, Last Modified: 21 Oct 2025
- NPGML Poster
- Readers: Everyone