Yuxuan Liang

Orcid: 0000-0003-2817-7337

According to our database1, Yuxuan Liang authored at least 157 papers between 2016 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2025
Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook.
Inf. Fusion, 2025

2024
Flipover outperforms dropout in deep learning.
Vis. Comput. Ind. Biomed. Art, December, 2024

A Survey on Service Route and Time Prediction in Instant Delivery: Taxonomy, Progress, and Prospects.
IEEE Trans. Knowl. Data Eng., December, 2024

Decoupling Long- and Short-Term Patterns in Spatiotemporal Inference.
IEEE Trans. Neural Networks Learn. Syst., November, 2024

Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey.
IEEE Trans. Knowl. Data Eng., October, 2024

Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects.
IEEE Trans. Pattern Anal. Mach. Intell., October, 2024

Predictability in Human Mobility: From Individual to Collective (Vision Paper).
ACM Trans. Spatial Algorithms Syst., June, 2024

Predicting Collective Human Mobility via Countering Spatiotemporal Heterogeneity.
IEEE Trans. Mob. Comput., May, 2024

Brave the Wind and the Waves: Discovering Robust and Generalizable Graph Lottery Tickets.
IEEE Trans. Pattern Anal. Mach. Intell., May, 2024

End-to-End Delay Modeling via Leveraging Competitive Interaction Among Network Flows.
IEEE Trans. Netw. Serv. Manag., April, 2024

Air Quality Prediction with Physics-Informed Dual Neural ODEs in Open Systems.
CoRR, 2024

GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning.
CoRR, 2024

Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting.
CoRR, 2024

Towards Neural Scaling Laws for Time Series Foundation Models.
CoRR, 2024

Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts.
CoRR, 2024

Toward Physics-guided Time Series Embedding.
CoRR, 2024

Mind Scramble: Unveiling Large Language Model Psychology Via Typoglycemia.
CoRR, 2024

Spatial-Temporal Mixture-of-Graph-Experts for Multi-Type Crime Prediction.
CoRR, 2024

Navigating Spatio-Temporal Heterogeneity: A Graph Transformer Approach for Traffic Forecasting.
CoRR, 2024

Unlocking the Power of LSTM for Long Term Time Series Forecasting.
CoRR, 2024

PetalView: Fine-grained Location and Orientation Extraction of Street-view Images via Cross-view Local Search with Supplementary Materials.
CoRR, 2024

TSI-Bench: Benchmarking Time Series Imputation.
CoRR, 2024

TwinS: Revisiting Non-Stationarity in Multivariate Time Series Forecasting.
CoRR, 2024

Predicting Parking Availability in Singapore with Cross-Domain Data: A New Dataset and A Data-Driven Approach.
CoRR, 2024

Time-SSM: Simplifying and Unifying State Space Models for Time Series Forecasting.
CoRR, 2024

NuwaTS: a Foundation Model Mending Every Incomplete Time Series.
CoRR, 2024

Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting.
CoRR, 2024

Learning Geospatial Region Embedding with Heterogeneous Graph.
CoRR, 2024

All Nodes are created Not Equal: Node-Specific Layer Aggregation and Filtration for GNN.
CoRR, 2024

A Survey on Diffusion Models for Time Series and Spatio-Temporal Data.
CoRR, 2024

Low-rank Adaptation for Spatio-Temporal Forecasting.
CoRR, 2024

Personalized Federated Learning for Spatio-Temporal Forecasting: A Dual Semantic Alignment-Based Contrastive Approach.
CoRR, 2024

UrbanVLP: A Multi-Granularity Vision-Language Pre-Trained Foundation Model for Urban Indicator Prediction.
CoRR, 2024

Deep Learning for Trajectory Data Management and Mining: A Survey and Beyond.
CoRR, 2024

Spatio-Temporal Fluid Dynamics Modeling via Physical-Awareness and Parameter Diffusion Guidance.
CoRR, 2024

OverleafCopilot: Empowering Academic Writing in Overleaf with Large Language Models.
CoRR, 2024

DynST: Dynamic Sparse Training for Resource-Constrained Spatio-Temporal Forecasting.
CoRR, 2024

Spatio-Temporal Field Neural Networks for Air Quality Inference.
CoRR, 2024

ComS2T: A complementary spatiotemporal learning system for data-adaptive model evolution.
CoRR, 2024

Deep Learning for Cross-Domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlook.
CoRR, 2024

BiVRec: Bidirectional View-based Multimodal Sequential Recommendation.
CoRR, 2024

Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective.
CoRR, 2024

Modeling Spatio-temporal Dynamical Systems with Neural Discrete Learning and Levels-of-Experts.
CoRR, 2024

Deep Learning for Multivariate Time Series Imputation: A Survey.
CoRR, 2024

Position Paper: What Can Large Language Models Tell Us about Time Series Analysis.
CoRR, 2024

Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classification.
CoRR, 2024

UrbanCLIP: Learning Text-enhanced Urban Region Profiling with Contrastive Language-Image Pretraining from the Web.
Proceedings of the ACM on Web Conference 2024, 2024

COLA: Cross-city Mobility Transformer for Human Trajectory Simulation.
Proceedings of the ACM on Web Conference 2024, 2024

UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting.
Proceedings of the ACM on Web Conference 2024, 2024

CityCAN: Causal Attention Network for Citywide Spatio-Temporal Forecasting.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Reinventing Node-centric Traffic Forecasting for Improved Accuracy and Efficiency.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

UrbanCross: Enhancing Satellite Image-Text Retrieval with Cross-Domain Adaptation.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

ControlTraj: Controllable Trajectory Generation with Topology-Constrained Diffusion Model.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

LaDe: The First Comprehensive Last-mile Express Dataset from Industry.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

The Snowflake Hypothesis: Training and Powering GNN with One Node One Receptive Field.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Foundation Models for Time Series Analysis: A Tutorial and Survey.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

The 13th International Workshop on Urban Computing.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Cluster-Wide Task Slowdown Detection in Cloud System.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

GSDI: Spatio-Temporal Contrastive Learning for Geo-Sensory Data Inference.
Proceedings of the International Joint Conference on Neural Networks, 2024

Predicting Carpark Availability in Singapore with Cross-Domain Data: A New Dataset and A Data-Driven Approach.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Spatio-Temporal Field Neural Networks for Air Quality Inference.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Position: What Can Large Language Models Tell Us about Time Series Analysis.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Graph Lottery Ticket Automated.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Urban Sensing for Multi-Destination Workers via Deep Reinforcement Learning.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

HGAMLP: Heterogeneous Graph Attention MLP with De-Redundancy Mechanism.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Learning Multi-Pattern Normalities in the Frequency Domain for Efficient Time Series Anomaly Detection.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Fall Prediction by a Spatio-Temporal Multi-Channel Causal Model from Wearable Sensors Data.
Proceedings of the IEEE International Conference on Acoustics, 2024

Towards Unifying Diffusion Models for Probabilistic Spatio-Temporal Graph Learning.
Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems, 2024

SENCR: A Span Enhanced Two-Stage Network with Counterfactual Rethinking for Chinese NER.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Earthfarsser: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

MSGNet: Learning Multi-Scale Inter-series Correlations for Multivariate Time Series Forecasting.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Mixed-Order Relation-Aware Recurrent Neural Networks for Spatio-Temporal Forecasting.
IEEE Trans. Knowl. Data Eng., September, 2023

EGraph: Efficient Concurrent GPU-Based Dynamic Graph Processing.
IEEE Trans. Knowl. Data Eng., June, 2023

AutoSTG<sup>+</sup>: An automatic framework to discover the optimal network for spatio-temporal graph prediction.
Artif. Intell., May, 2023

Earthfarseer: Versatile Spatio-Temporal Dynamical Systems Modeling in One Model.
CoRR, 2023

Rethinking Urban Mobility Prediction: A Super-Multivariate Time Series Forecasting Approach.
CoRR, 2023

MACE: A Multi-pattern Accommodated and Efficient Anomaly Detection Method in the Frequency Domain.
CoRR, 2023

Attend Who is Weak: Enhancing Graph Condensation via Cross-Free Adversarial Training.
CoRR, 2023

When Urban Region Profiling Meets Large Language Models.
CoRR, 2023

Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook.
CoRR, 2023

The Snowflake Hypothesis: Training Deep GNN with One Node One Receptive field.
CoRR, 2023

Beyond Geo-localization: Fine-grained Orientation of Street-view Images by Cross-view Matching with Satellite Imagery with Supplementary Materials.
CoRR, 2023

LaDe: The First Comprehensive Last-mile Delivery Dataset from Industry.
CoRR, 2023

Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects.
CoRR, 2023

Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey.
CoRR, 2023

DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models.
CoRR, 2023

Do We Really Need Graph Neural Networks for Traffic Forecasting?
CoRR, 2023

Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PetalView: Fine-grained Location and Orientation Extraction of Street-view Images via Cross-view Local Search.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

Maintaining the Status Quo: Capturing Invariant Relations for OOD Spatiotemporal Learning.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Graph Neural Processes for Spatio-Temporal Extrapolation.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Contrastive Trajectory Similarity Learning with Dual-Feature Attention.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models.
Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems, 2023

Primacy Effect of ChatGPT.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

How Fragile is Relation Extraction under Entity Replacements?
Proceedings of the 27th Conference on Computational Natural Language Learning, 2023

AirFormer: Predicting Nationwide Air Quality in China with Transformers.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Visual Cascade Analytics of Large-Scale Spatiotemporal Data.
IEEE Trans. Vis. Comput. Graph., 2022

Predicting Citywide Crowd Flows in Irregular Regions Using Multi-View Graph Convolutional Networks.
IEEE Trans. Knowl. Data Eng., 2022

Spatio-Temporal Meta Learning for Urban Traffic Prediction.
IEEE Trans. Knowl. Data Eng., 2022

Fine-Grained Urban Flow Inference.
IEEE Trans. Knowl. Data Eng., 2022

GGraph: An Efficient Structure-Aware Approach for Iterative Graph Processing.
IEEE Trans. Big Data, 2022

Predicting Urban Water Quality With Ubiquitous Data - A Data-Driven Approach.
IEEE Trans. Big Data, 2022

Federated Forest.
IEEE Trans. Big Data, 2022

VECtor: A Versatile Event-Centric Benchmark for Multi-Sensor SLAM.
IEEE Robotics Autom. Lett., 2022

Content-Attribute Disentanglement for Generalized Zero-Shot Learning.
IEEE Access, 2022

Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

GraphCache: Message Passing as Caching for Sentence-Level Relation Extraction.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

Beyond Geo-localization: Fine-grained Orientation of Street-view Images by Cross-view Matching with Satellite Imagery.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Time-Aware Neighbor Sampling on Temporal Graphs.
Proceedings of the International Joint Conference on Neural Networks, 2022

Periodic residual learning for crowd flow forecasting.
Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022

When do contrastive learning signals help spatio-temporal graph forecasting?
Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022

DualFormer: Local-Global Stratified Transformer for Efficient Video Recognition.
Proceedings of the Computer Vision - ECCV 2022, 2022

Optimal battery selection for solar storage system.
Proceedings of the International Conference on Computers, 2022

TrajFormer: Efficient Trajectory Classification with Transformers.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021
Time-Aware Neighbor Sampling for Temporal Graph Networks.
CoRR, 2021

PRNet: A Periodic Residual Learning Network for Crowd Flow Forecasting.
CoRR, 2021

Structure-Aware Label Smoothing for Graph Neural Networks.
CoRR, 2021

Phase function estimation from a diffuse optical image via deep learning.
CoRR, 2021

Decoupling Long- and Short-Term Patterns in Spatiotemporal Inference.
CoRR, 2021

Spatio-Temporal Graph Contrastive Learning.
CoRR, 2021

Mixup for Node and Graph Classification.
Proceedings of the WWW '21: The Web Conference 2021, 2021

CurGraph: Curriculum Learning for Graph Classification.
Proceedings of the WWW '21: The Web Conference 2021, 2021

AutoSTG: Neural Architecture Search for Predictions of Spatio-Temporal Graph✱.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Fine-Grained Urban Flow Prediction.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Adaptive Data Augmentation on Temporal Graphs.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Directed Graph Contrastive Learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Learning Multi-context Aware Location Representations from Large-scale Geotagged Images.
Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Modeling Trajectories with Neural Ordinary Differential Equations.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

2020
Dynamic Public Resource Allocation Based on Human Mobility Prediction.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2020

GraphCrop: Subgraph Cropping for Graph Classification.
CoRR, 2020

Directed Graph Convolutional Network.
CoRR, 2020

Revisiting Convolutional Neural Networks for Urban Flow Analytics.
CoRR, 2020

Progressive Supervision for Node Classification.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Revisiting Convolutional Neural Networks for Citywide Crowd Flow Analytics.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Digraph Inception Convolutional Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

NodeAug: Semi-Supervised Node Classification with Data Augmentation.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

AutoST: Efficient Neural Architecture Search for Spatio-Temporal Prediction.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Unsupervised Learning of Disentangled Location Embeddings.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Learning to Generate Maps from Trajectories.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

UrbanFM: Inferring Fine-Grained Urban Flows.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Learning Multi-Objective Rewards and User Utility Function in Contextual Bandits for Personalized Ranking.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018
HyperST-Net: Hypernetworks for Spatio-Temporal Forecasting.
CoRR, 2018

GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction.
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017
M-NSGA-II: A Memetic Algorithm for Vehicle Routing Problem with Route Balancing.
Proceedings of the Advances in Artificial Intelligence: From Theory to Practice, 2017

Inferring Traffic Cascading Patterns.
Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2017

2016
Predicting Urban Water Quality with Ubiquitous Data.
CoRR, 2016

Urban Water Quality Prediction Based on Multi-Task Multi-View Learning.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016


  Loading...