MCM-DM: Towards Better Spatio-Temporal Event Representation Learning via Discrete Morse Theory
Y. Zhang, J. Rozenblit, C. Yang, J. Goel, Y. Gel, and Y. Chen
Advances in Neural Information Processing Systems (NeurIPS) 2026
Beyond Local Neighborhoods: Fractional Diffusion with Levy Flights on Simplicial Complexes for Link Prediction
J. Goel, Y. Chen, K. Avrachenkov, and Y. Gel
Advances in Neural Information Processing Systems (NeurIPS) 2026
Multimodal Alignment and Uncertainty Quantification for Power Outage Forecasting
X. Hou, Y. Chen, and L. Du
ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SigSpatial) 2026
Uncertainty-aware Multi-modality Spatio-temporal Wildfire and Smoke Prediction
Y. Zhang, C. Yang, N. LaHaye, H. Lee, Y. Gel, and Y. Chen
ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SigSpatial) 2026
Large Language Models as Topological Thinkers: A Benchmark on Graph Persistent Homology
H. Li, H. Wan, Y. Huang, Y. Chen, Y. Gel, and H. Jiang
In Proceedings of the International Conference on Machine Learning (ICML) 2026
A Spatio-Temporal Neural Network for Long-Term Load Profile Forecasting with Topological Information
F. An, N. Yu, Z. Shao, Y. Chen, A. Rahman, C. Burleyson, K. Oikonomou, and O. Anderson
IEEE Power and Energy Society General Meeting (PESGM) 2026
Adaptive Domain Shift in Diffusion Models for Cross-Modality Image Translation
Z. Wang, Y. Chen, and S. Ren
In Proceedings of the International Conference on Learning Representations (ICLR) 2026
TEN-DM: Topology-Enhanced Diffusion Model for Spatio-Temporal Event Prediction
Y. Liu, K. Wang, C. Yang, Y. Gel, and Y. Chen
In Proceedings of the International Conference on Learning Representations (ICLR) 2026
Multi-Modal Enhanced Graph Transfer Learning for Digital Finance Fraud Detection
Y. Liu, S. Chan, Y. Zhang, J. Chu, C. Yang, Z. Wang, Y. Gel, and Y. Chen
In Proceedings of the ACM Web Conference (WWW) 2026
Bringing Shape to Spatio-Temporal Graph Contrastive Learning
Y. Chen, and Y. Gel
In Proceedings of the IEEE International Conference on Big Data (BigData) 2025
Topology-Induced Graph Transformer for Graph Representation Learning
P. Liang, Y. Chen, and X. He
In Proceedings of the IEEE International Conference on Big Data (BigData) 2025
Understanding the Impact of Environmental Contexts on Lung Cancer with Simplicial Representation Learning and Remote Sensing
J. Yang, Y. Chen, C. Tribby, L. Erhunmwunsee, C. Thompson, T. Benmarhnia, H. Lee, M. Jankowska, and Y. Gel
In Proceedings of the IEEE International Conference on Big Data (BigData) 2025
When LLM Meets Simplicial Complex: A Novel Graph Prompt Learning on Ethereum Transaction Networks
Y. Liu, S. Chan, Y. Zhang, J. Chu, and Y. Chen
In Proceedings of the IEEE International Conference on Data Mining (ICDM) 2025
LLM-Based Multi-Agent System and Simplicial Self-Supervised Learning Model for Regional Cancer Prevalence Estimation Using Satellite Imagery
J. Yang, Y. Chen, C. Tribby, H. Lee, L. Erhunmwunsee, T. Benmarhnia, C. Thompson, Y. Gel, and M. Jankowska
ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SigSpatial) 2025
TMetaNet: Topological Meta-Learning Framework for Dynamic Link Prediction
H. Li, H. Wan, Y. Chen, D. Ye, Y. Gel, and H. Jiang
In Proceedings of the International Conference on Machine Learning (ICML) 2025
Topological Zigzag Spaghetti for Diffusion-based Generation and Prediction on Graphs
Y. Chen, and Y. Gel
In Proceedings of the International Conference on Learning Representations (ICLR) 2025
Few-shot Learning over Graphs Using Topological Prompts
J. Goel, Y. Chen, and Y. Gel
In Proceedings of the ACM Web Conference (WWW) 2025
Conditional Prediction ROC Bands for Graph Classification
Y. Wu, B. Yang, E. Chen, Y. Chen, and Z. Zhen
In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 2025
Topology-Informed Pre-training of Graph Neural Networks
P. Liang, Y. Gel, and Y. Chen
In Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2025
Fusing Multimodality of Large Language Models and Satellite Imagery via Simplicial Contrastive Learning for Latent Urban Feature Identification and Environmental Application
Y. Chen, J. Yang, H. Lee, C. Tribby, T. Benmarhnia, M. Jankowska, and Y. Gel
In Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2025
Safety and Public Protection: Predicting and Analyzing Incidents with Large Language Model-Based Zigzag Graph Neural Networks
H. Shafei, Y. Zhao, C. Martin, J. Alizadeh, K. Eyrich-Garg, O. Martinez, Y. Ding, C. Tan, H. Wu, and Y. Chen
In Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2025
When Witnesses Defend: A Witness Graph Topological Layer for Adversarial Graph Learning
N. Arafat, D. Basu, Y. Gel, and Y. Chen
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2025
Firecast Zigzag Convolutional Network for Wildfire Prediction
Y. Chen, J. Castillo, H. Lee, and Y. Gel
In IEEE International Conference on Big Data (BigData) 2024
Multi-view K-Nearest Neighbor Graph Contrastive Learning on Multi-modal Biomedical Data
Y. Zhang, S. Chen, R. Mccoy, C. Chen, and Y. Chen
In Proceedings of the International Conference on Artificial Intelligence in Medicine (AIME) 2024
Revisiting Link Prediction with the Dowker Complex
J. Choi, Y. Chen, J. Frias, J. Castillo, and Y. Gel
In Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2024
SNN-PDE: Learning Dynamic PDEs from Data with Simplicial Neural Networks
J. Choi, Y. Chen, H. Lee, H. Kim, and Y. Gel
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2024
Time-Aware Knowledge Representations of Dynamic Objects with Multidimensional Persistence
B. Coskunuzer, I. Segovia-Dominguez, Y. Chen, and Y. Gel
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2024
Tensor-view Topological Graph Neural Network
T. Wen, E. Chen, and Y. Chen
In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 2024
Learning Power System Vulnerabilities through Multi-View Topological Neural Networks
Y. Chen, S. Wang, and L. Du
IEEE Power & Energy Society General Meeting (PESGM) 2024
TopoGCL: Topological Graph Contrastive Learning
Y. Chen, J. Frias, and Y. Gel
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2024
United We Stand, Divided We Fall: Networks to Graph (N2G) Abstraction for Robust Graph Classification under Graph Label Corruption
Z. Zhen, Y. Chen, M. Kantarcioglu, Y. Gel, and K. Jee
In Proceedings of the Learning on Graphs Conference (LoG) 2023
EMP: Effective Multidimensional Persistence for Graph Representation Learning
Y. Chen, I. Segovia-Dominguez, C. Akcora, Z. Zhen, M. Kantarcioglu, Y. Gel, and B. Coskunuzer
In Proceedings of the Learning on Graphs Conference (LoG) 2023
H^2-Nets: Hyper-hodge Convolutional Neural Networks for Time-Series Forecasting
Y. Chen, T. Jiang, and Y. Gel
In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 2023
Modeling and Classification of EV Charging Profiles Utilizing Topological Data Analysis
Z. Zhao, Y. Chen, and L. Du
IEEE Transportation Electrification Conference & Expo (ITEC+) 2023
Higher-Order Spatio-Temporal Neural Networks for Covid-19 Forecasting
Y. Chen, S. Batsakis, and H. Vincent Poor
IEEE International Conference on Acoustics, Speech and Signal (ICASSP) 2023
AP-GNN: Unsupervised Adaptive Distribution Grid-Level Representation Learning
Y. Chen, M. Heleno, A. Moreira, and Y. Gel
IEEE PowerTech 2023
Topological Graph Convolutional Networks Solutions for Power Distribution Grid Planning
Y. Chen, M. Heleno, A. Moreira, and Y. Gel
In Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2023
Topological Pooling on Graphs
Y. Chen, and Y. Gel
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2023
Efficient Planning of Multi-Robot Collective Transport using Graph Reinforcement Learning with Higher Order Topological Abstraction
S. Paul, W. Li, B. Smyth, Y. Chen, Y. Gel, and S. Chowdhury
In Proceedings of the International Conference on Robotics and Automation (ICRA) 2023
Learning on Health Fairness and Environmental Justice via Interactive Visualization
A. Nayeem, I. Segovia-Dominguez, H. Lee, D. Han, Y. Chen, Z. Zhen, Y. Gel, and I. Cho
In Proceedings of the IEEE International Conference on Big Data (BigData) 2022
Evaluating Distribution System Reliability with Hyperstructures Graph Convolutional Nets
Y. Chen, T. Jiang, M. Heleno, A. Moreira, and Y. Gel
In Proceedings of the IEEE International Conference on Big Data (BigData) 2022
Tlife-GDN: Detecting and Forecasting Spatio-Temporal Anomalies via Persistent Homology and Geometric Deep Learning
Z. Zhen, Y. Chen, I. Segovia-Dominguez, and Y. Gel
In Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2022
TAMP-S2GCNets: When Time-Aware Multipersistence Meets Spatio-Supra Graph Convolutional Nets while Forecasting Time Series
Y. Chen, I. Segovia-Dominguez, B. Coskunuzer, and Y. Gel
In Proceedings of the International Conference on Learning Representations (ICLR) 2022
Time-Conditioned Dances with Simplicial Complexes: Zigzag Filtration Curve based Supra-Hodge Convolution Networks for Time-series Forecasting
Y. Chen, Y. Gel, and H. Vincent Poor
Advances in Neural Information Processing Systems (NeurIPS) 2022
ToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery
A. Demir, B. Coskunuzer, I. Segovia-Dominguez, Y. Chen, Y. Gel, and B. Kiziltan
Advances in Neural Information Processing Systems (NeurIPS) 2022
TopoAttn-Nets: Topological Attention in Graph Representation Learning
Y. Chen, E. Sizikova, and Y. Gel
In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 2022
TCN: Pioneering Topological-Based Convolutional Networks for Planetary Terrain Learning
Y. Chen, Y. Marchetti, E. Sizikova, and Y. Gel
In Proceedings of the Innovative Applications of Artificial Intelligence Conference (AAAI/IAAI) 2022
BScNets: Block Simplicial Complex Neural Networks
Y. Chen, Y. Gel, and H. Vincent Poor
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2022
Topological Relational Learning on Graphs
Y. Chen, B. Coskunuzer, and Y. Gel
Advances in Neural Information Processing Systems (NeurIPS) 2021
Does Air Quality Really Impact COVID-19 Clinical Severity: Coupling NASA Satellite Datasets with Geometric Deep Learning
I. Segovia Dominguez, H. Lee, Y. Chen, M. Garay, K. Gorski, and Y. Gel
In Proceedings of the ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD) 2021
Deepening the Sense of Touch in Planetary Exploration with Geometric and Topological Deep Learning
Y. Chen, Y. Marchetti, and Y. Gel
In Proceedings of the Innovative Applications of Artificial Intelligence Conference (AAAI/IAAI) 2021
Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting
Y. Chen, I. Segovia-Dominguez, and Y. Gel
In Proceedings of the International Conference on Machine Learning (ICML) 2021
Topological machine learning methods for power system responses to contingencies
B. Bush, Y. Chen, D. Ofori-Boateng, and Y. Gel
In Proceedings of the Innovative Applications of Artificial Intelligence Conference (AAAI/IAAI) 2021
LFGCN: Levitating over Graphs with Levy Flights
Y. Chen, Y. Gel, and K. Avrachenkov
In Proceedings of the IEEE International Conference on Data Mining (ICDM) 2020
Deep ensemble classifiers and peer effects analysis for churn forecasting in retail banking
Y. Chen, Y. Gel, V. Lyubchich, and T. Winship
In Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2018
GridGraph-LLM: A grid topology and graph-aware large language model for contingency analysis and transmission outage localization
M. Chen, L. Du, and Y. Chen
Applied Energy
Multilayer topology-aware graph contrastive learning for fraud detection in the Ethereum transaction network
Y. Chen, Y. Zhang, S. Chan, J. Chu, and N. Lord
Journal of the Royal Statistical Society, Series A 2025
Stochastic Block Model-Aware Topological Neural Networks for Graph Link Prediction
Y. Chen, X. Guo, and S. Ma
Transactions on Machine Learning Research 2025
Understanding Power Grid Network Vulnerability through the Stochastic Lens of Network Motif Evolution
Y. Chen, H. Ng, Y. Gel, and H. Vincent Poor
Journal of the Royal Statistical Society, Series C 2024
Topological K-Means Clustering in Reproducing Kernel Hilbert Spaces
M. Dixon, Y. Gel, and Y. Chen
Electronic Journal of Statistics 2024
Mutual Information Guided Diffusion for Zero-shot Cross-modality Medical Image Translation
Z. Wang, Y. Yang, Y. Chen, T. Yuan, M. Sermesant, H. Delingette, and O. Wu
IEEE Transactions on Medical Imaging 2024
Statistical Models and Algorithms for Assessing Robustness and Reliability of Networks with Applications in Cybersecurity Insurance
Y. Chen, and H. Ng
Variance 2024
Environmental Justice and Lessons Learned from COVID-19 Outcomes–Uncovering Hidden Patterns with Geometric Deep Learning and New NASA Satellite Data
Z. Zhen, H. Lee, I. Segovia-Dominguez, M. Huang, Y. Chen, M. Garay, D. Crichton, and Y. Gel
Artificial Intelligence for the Earth Systems 2024
Learning Power Grid Outages with Higher-Order Topological Neural Networks
Y. Chen, R. Jacob, Y. Gel, J. Zhang, and H. Vincent Poor
IEEE Transactions on Power Systems 2023
Seven Open Problems in Applied Combinatorics
S. Aksoy, R. Bennink, Y. Chen, J. Frías, Y. Gel, B. Kay, U. Naumann, C. Marrero, A. Petyuk, S. Roy, I. Segovia-Dominguez, N. Veldt, and S. Young
Journal of Combinatorics 2023
Self-Supervised Contrastive Learning for Wildfire Detection: Utility and Limitations
J. Choi, N. LaHaye, Y. Chen, H. Lee, and Y. Gel
Advances in Machine Learning and Image Analysis for GeoAI 2024