Yuzhou Chen

This page is a disambiguation page, it actually contains mutiple papers from persons of the same or a similar name.

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Bibliography

2025
Rethinking shrinking cities through urban flows: Network-based insights into coordinated development.
Urban Inform., December, 2025

An Efficient Multi-View Cross-Attention Accelerator for Vision-Centric 3D Perception in Autonomous Driving.
IEEE Trans. Circuits Syst. I Regul. Pap., July, 2025

Neural Rendering Acceleration With Deferred Neural Decoding and Voxel-Centric Data Flow.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., July, 2025

POLARIS: A High-contrast Polarimetric Imaging Benchmark Dataset for Exoplanetary Disk Representation Learning.
CoRR, June, 2025

TMetaNet: Topological Meta-Learning Framework for Dynamic Link Prediction.
CoRR, June, 2025

Addressing the fixed effects in gravity model based on higher-order origin-destination pairs.
Int. J. Geogr. Inf. Sci., May, 2025

Stochastic Block Model-Aware Topological Neural Networks for Graph Link Prediction.
Trans. Mach. Learn. Res., 2025

Few-shot Learning over Graphs Using Topological Prompts.
Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

Tensor-Fused Multi-view Graph Contrastive Learning.
Proceedings of the Data Science: Foundations and Applications, 2025

Safety and Public Protection: Predicting and Analyzing Incidents with Large Language Model-Based Zigzag Graph Neural Networks.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2025

Topological Zigzag Spaghetti for Diffusion-based Generation and Prediction on Graphs.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Topology-Informed Pre-training of Graph Neural Networks.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

Fusing Multimodality of Large Language Models and Satellite Imagery via Simplicial Contrastive Learning for Latent Urban Feature Identification and Environmental Application.
Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation.
Proceedings of the Conference on Parsimony and Learning, 2025

Conditional Prediction ROC Bands for Graph Classification.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

When Witnesses Defend: A Witness Graph Topological Layer for Adversarial Graph Learning.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
Mutual Information Guided Diffusion for Zero-Shot Cross-Modality Medical Image Translation.
IEEE Trans. Medical Imaging, August, 2024

A Broad-Spectrum and High-Throughput Compression Engine for Neural Network Processors.
IEEE Trans. Circuits Syst. II Express Briefs, July, 2024

Fire-D: Analysis and ML-Ready NASA-Centric Remote Sensing of Wildfire and Smoke.
Dataset, June, 2024

Motivations behind problematic short video use: A three-level meta-analysis.
Telematics Informatics, 2024

Research on airport baggage anomaly retention detection technology based on machine vision, edge computing, and blockchain.
IET Blockchain, 2024

Predicting Emergency Department Visits for Patients with Type II Diabetes.
CoRR, 2024

TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time Series Forecasting.
CoRR, 2024

Conditional Uncertainty Quantification for Tensorized Topological Neural Networks.
CoRR, 2024

HumanFT: A Human-like Fingertip Multimodal Visuo-Tactile Sensor.
CoRR, 2024

Diffusion based Zero-shot Medical Image-to-Image Translation for Cross Modality Segmentation.
CoRR, 2024

Revisiting Link Prediction with the Dowker Complex.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2024

Fragile Earth: Generative and Foundational Models for Sustainable Development.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

A High-Throughput Lossless Image Compression Engine Optimized for Compression Ratio.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2024

VEGA: Implementing a Versatile and Efficient Deep Learning Processor with Graph-Based ALU.
Proceedings of the 42nd IEEE International Conference on Computer Design, 2024

DEFA: Efficient Deformable Attention Acceleration via Pruning-Assisted Grid-Sampling and Multi-Scale Parallel Processing.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

Firecast Zigzag Convolutional Network for Wildfire Prediction.
Proceedings of the IEEE International Conference on Big Data, 2024

Tensor-view Topological Graph Neural Network.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Multi-view k-Nearest Neighbor Graph Contrastive Learning on Multi-modal Biomedical Data.
Proceedings of the Artificial Intelligence in Medicine - 22nd International Conference, 2024

Time-Aware Knowledge Representations of Dynamic Objects with Multidimensional Persistence.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

SNN-PDE: Learning Dynamic PDEs from Data with Simplicial Neural Networks.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

TopoGCL: Topological Graph Contrastive Learning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
A space-time flow LISA approach for panel flow data.
Comput. Environ. Urban Syst., December, 2023

Exploring the spatiotemporal relationships between search flows and travel flows.
Trans. GIS, August, 2023

Seven open problems in applied combinatorics.
CoRR, 2023

H<sup>2</sup>-Nets: Hyper-hodge Convolutional Neural Networks for Time-Series Forecasting.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Topological Graph Convolutional Networks Solutions for Power Distribution Grid Planning.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

United We Stand, Divided We Fall: Networks to Graph (N2G) Abstraction for Robust Graph Classification Under Graph Label Corruption.
Proceedings of the Learning on Graphs Conference, 27-30 November 2023, Virtual Event., 2023

EMP: Effective Multidimensional Persistence for Graph Representation Learning.
Proceedings of the Learning on Graphs Conference, 27-30 November 2023, Virtual Event., 2023

Fragile Earth: AI for Climate Sustainability - From Wildfire Disaster Management to Public Health and Beyond.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

O<sup>3</sup>NMS: An Out-Of-Order-Based Low-Latency Accelerator for Non-Maximum Suppression.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2023

Efficient Planning of Multi-Robot Collective Transport using Graph Reinforcement Learning with Higher Order Topological Abstraction.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

SpOctA: A 3D Sparse Convolution Accelerator with Octree-Encoding-Based Map Search and Inherent Sparsity-Aware Processing.
Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023

Higher-Order Spatio-Temporal Neural Networks for Covid-19 Forecasting.
Proceedings of the IEEE International Conference on Acoustics, 2023

FLNA: An Energy-Efficient Point Cloud Feature Learning Accelerator with Dataflow Decoupling.
Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

Graph of Graphs: A New Knowledge Representation Mechanism for Graph Learning (Student Abstract).
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Topological Pooling on Graphs.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
A new urban change detection method based on the local G and local spatial heteroscedasticity statistics.
Trans. GIS, 2022

TopoAttn-Nets: Topological Attention in Graph Representation Learning.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

Tlife-GDN: Detecting and Forecasting Spatio-Temporal Anomalies via Persistent Homology and Geometric Deep Learning.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

ToDD: Topological Compound Fingerprinting in Computer-Aided Drug Discovery.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Time-Conditioned Dances with Simplicial Complexes: Zigzag Filtration Curve based Supra-Hodge Convolution Networks for Time-series Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning on Health Fairness and Environmental Justice via Interactive Visualization.
Proceedings of the IEEE International Conference on Big Data, 2022

Evaluating Distribution System Reliability with Hyperstructures Graph Convolutional Nets.
Proceedings of the IEEE International Conference on Big Data, 2022

TCN: Pioneering Topological-Based Convolutional Networks for Planetary Terrain Learning.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

BScNets: Block Simplicial Complex Neural Networks.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Using NASA Satellite Data Sources and Geometric Deep Learning to Uncover Hidden Patterns in COVID-19 Clinical Severity.
CoRR, 2021

Topological Relational Learning on Graphs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Does Air Quality Really Impact COVID-19 Clinical Severity: Coupling NASA Satellite Datasets with Geometric Deep Learning.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting.
Proceedings of the 38th International Conference on Machine Learning, 2021

Deepening the Sense of Touch in Planetary Exploration with Geometric and Topological Deep Learning.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Topological Machine Learning Methods for Power System Responses to Contingencies.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Examining spatial accessibility to COVID-19 testing sites in Florida.
Ann. GIS, 2020

LFGCN: Levitating over Graphs with Levy Flights.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019
Deep Learning Ethereum Token Price Prediction with Network Motif Analysis.
Proceedings of the 2019 International Conference on Data Mining Workshops, 2019

2018
Snowboot: Bootstrap Methods for Network Inference.
R J., 2018

Deep Ensemble Classifiers and Peer Effects Analysis for Churn Forecasting in Retail Banking.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018


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