Bin Yang

Orcid: 0000-0002-1658-1079

Affiliations:
  • East China Normal University, China
  • Aalborg University, Denmark
  • Aarhus University, Denmark (2011-2014)
  • Max Planck Institut für Informatik, Germany (2010-2011)
  • Fudan University, China (2007-2010, PhD)


According to our database1, Bin Yang authored at least 154 papers between 2008 and 2024.

Collaborative distances:

Timeline

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Bibliography

2024
Adversarial Graph Neural Network for Multivariate Time Series Anomaly Detection.
IEEE Trans. Knowl. Data Eng., December, 2024

Editorial: DSAA 2023 journal track on theoretical and practical data science and analytics.
Int. J. Data Sci. Anal., October, 2024

AutoCTS++: zero-shot joint neural architecture and hyperparameter search for correlated time series forecasting.
VLDB J., September, 2024

Efficient Stochastic Routing in Path-Centric Uncertain Road Networks.
Proc. VLDB Endow., July, 2024

QCore: Data-Efficient, On-Device Continual Calibration for Quantized Models.
Proc. VLDB Endow., July, 2024

Multi-granularity attention in attention for person re-identification in aerial images.
Vis. Comput., June, 2024

TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods.
Proc. VLDB Endow., May, 2024

Coalition-based task assignment with priority-aware fairness in spatial crowdsourcing.
VLDB J., January, 2024

Less is More: Efficient Time Series Dataset Condensation via Two-fold Modal Matching-Extended Version.
CoRR, 2024

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

TEAM: Topological Evolution-aware Framework for Traffic Forecasting-Extended Version.
CoRR, 2024

Unsupervised Time Series Anomaly Prediction with Importance-based Generative Contrastive Learning.
CoRR, 2024

MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast.
CoRR, 2024

DiffImp: Efficient Diffusion Model for Probabilistic Time Series Imputation with Bidirectional Mamba Backbone.
CoRR, 2024

CATCH: Channel-Aware multivariate Time Series Anomaly Detection via Frequency Patching.
CoRR, 2024

FoundTS: Comprehensive and Unified Benchmarking of Foundation Models for Time Series Forecasting.
CoRR, 2024

Orca: Ocean Significant Wave Height Estimation with Spatio-temporally Aware Large Language Models.
CoRR, 2024

Efficient Stochastic Routing in Path-Centric Uncertain Road Networks - Extended Version.
CoRR, 2024

ROSE: Register Assisted General Time Series Forecasting with Decomposed Frequency Learning.
CoRR, 2024

Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders.
CoRR, 2024

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

QCore: Data-Efficient, On-Device Continual Calibration for Quantized Models - Extended Version.
CoRR, 2024

GTM: General Trajectory Modeling with Auto-regressive Generation of Feature Domains.
CoRR, 2024

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

A Crystal Knowledge-Enhanced Pre-training Framework for Crystal Property Estimation.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2024

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

Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Routing with Massive Trajectory Data.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

A Unified Replay-Based Continuous Learning Framework for Spatio-Temporal Prediction on Streaming Data.
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Dependency-Aware Differentiable Neural Architecture Search.
Proceedings of the Computer Vision - ECCV 2024, 2024

Ocean Significant Wave Height Estimation with Spatio-temporally Aware Large Language Models.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
Stochastic Routing with Arrival Windows.
ACM Trans. Spatial Algorithms Syst., December, 2023

Multiple Time Series Forecasting with Dynamic Graph Modeling.
Proc. VLDB Endow., December, 2023

Weakly Guided Adaptation for Robust Time Series Forecasting.
Proc. VLDB Endow., December, 2023

CGF: A Category Guidance Based PM$_{2.5}$ Sequence Forecasting Training Framework.
IEEE Trans. Knowl. Data Eng., October, 2023

Multivariate Time Series Forecasting With Dynamic Graph Neural ODEs.
IEEE Trans. Knowl. Data Eng., September, 2023

Origin-Destination Travel Time Oracle for Map-based Services.
Proc. ACM Manag. Data, September, 2023

Profit Optimization in Spatial Crowdsourcing: Effectiveness and Efficiency.
IEEE Trans. Knowl. Data Eng., August, 2023

MagicScaler: Uncertainty-aware, Predictive Autoscaling.
Proc. VLDB Endow., 2023

AutoCTS+: Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting.
Proc. ACM Manag. Data, 2023

LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation.
Proc. ACM Manag. Data, 2023

A Summary of ICDE 2022 Research Session Panels.
IEEE Data Eng. Bull., 2023

A Crystal-Specific Pre-Training Framework for Crystal Material Property Prediction.
CoRR, 2023

LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation - Extended Version.
CoRR, 2023

LightPath: Lightweight and Scalable Path Representation Learning.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022
Context-Aware Path Ranking in Road Networks.
IEEE Trans. Knowl. Data Eng., 2022

Semantic driven attention network with attribute learning for unsupervised person re-identification.
Knowl. Based Syst., 2022

A Pattern Discovery Approach to Multivariate Time Series Forecasting.
CoRR, 2022

AutoPINN: When AutoML Meets Physics-Informed Neural Networks.
CoRR, 2022

Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting.
CoRR, 2022

A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis.
CoRR, 2022

Design Automation for Fast, Lightweight, and Effective Deep Learning Models: A Survey.
CoRR, 2022

Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting-Full Version.
CoRR, 2022

Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection - Extended Version.
CoRR, 2022

Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning - Extended Version.
CoRR, 2022

Towards Spatio-Temporal Aware Traffic Time Series Forecasting-Full Version.
CoRR, 2022

Influence-aware Task Assignment in Spatial Crowdsourcing (Technical Report).
CoRR, 2022

Outlier Detection for Streaming Task Assignment in Crowdsourcing.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Weighted Mutual Learning with Diversity-Driven Model Compression.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Interpreting Operation Selection in Differentiable Architecture Search: A Perspective from Influence-Directed Explanations.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

RetroGraph: Retrosynthetic Planning with Graph Search.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Anomaly Detection in Time Series with Robust Variational Quasi-Recurrent Autoencoders.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Towards Spatio- Temporal Aware Traffic Time Series Forecasting.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Influence-aware Task Assignment in Spatial Crowdsourcing.
Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Spatio-temporal graph convolutional network for stochastic traffic speed imputation.
Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 2022

BaLeNAS: Differentiable Architecture Search via the Bayesian Learning Rule.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Hyperverlet: A Symplectic Hypersolver for Hamiltonian Systems.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
AutoCTS: Automated Correlated Time Series Forecasting.
Proc. VLDB Endow., 2021

Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles.
Proc. VLDB Endow., 2021

AutoCTS: Automated Correlated Time Series Forecasting - Extended Version.
CoRR, 2021

Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles - Extended Version.
CoRR, 2021

Graph Attention Recurrent Neural Networks for Correlated Time Series Forecasting - Full version.
CoRR, 2021

Unsupervised Path Representation Learning with Curriculum Negative Sampling.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Fairness-aware Task Assignment in Spatial Crowdsourcing: Game-Theoretic Approaches.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

EnhanceNet: Plugin Neural Networks for Enhancing Correlated Time Series Forecasting.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

2020
Fast stochastic routing under time-varying uncertainty.
VLDB J., 2020

Context-aware, preference-based vehicle routing.
VLDB J., 2020

Anytime Stochastic Routing with Hybrid Learning.
Proc. VLDB Endow., 2020

Trajectory splicing.
Knowl. Inf. Syst., 2020

Force myography benchmark data for hand gesture recognition and transfer learning.
CoRR, 2020

Infinitely Wide Graph Convolutional Networks: Semi-supervised Learning via Gaussian Processes.
CoRR, 2020

A Road Segment Attribute Completion System.
Proceedings of the 21st IEEE International Conference on Mobile Data Management, 2020

A Correlated Time Series Forecast System.
Proceedings of the 21st IEEE International Conference on Mobile Data Management, 2020

Learning to Rank Paths in Spatial Networks.
Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

A Hybrid Learning Approach to Stochastic Routing.
Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

Stochastic Origin-Destination Matrix Forecasting Using Dual-Stage Graph Convolutional, Recurrent Neural Networks.
Proceedings of the 36th IEEE International Conference on Data Engineering, 2020

Estimating travel speed distributions of paths in road networks using dual-input LSTMs.
Proceedings of the IWCTS@SIGSPATIAL 2020: Proceedings of the 13th ACM SIGSPATIAL International Workshop on Computational Transportation Science, 2020

2019
Editorial: mobile data management and analytics.
GeoInformatica, 2019

PathRank: A Multi-Task Learning Framework to Rank Paths in Spatial Networks.
CoRR, 2019

A Practical Delivery Route Planning System.
Proceedings of the 20th IEEE International Conference on Mobile Data Management, 2019

A Charging Scheduling System for Electric Vehicles using Vehicle-to-Grid.
Proceedings of the 20th IEEE International Conference on Mobile Data Management, 2019

Outlier Detection for Time Series with Recurrent Autoencoder Ensembles.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Towards Longitudinal Analytics on Social Media Data.
Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

Stochastic Weight Completion for Road Networks Using Graph Convolutional Networks.
Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

2018
PACE: a PAth-CEntric paradigm for stochastic path finding.
VLDB J., 2018

Risk-aware path selection with time-varying, uncertain travel costs: a time series approach.
VLDB J., 2018

Finding Top-k Shortest Paths with Diversity.
IEEE Trans. Knowl. Data Eng., 2018

Recurrent Multi-Graph Neural Networks for Travel Cost Prediction.
CoRR, 2018

Correlated Time Series Forecasting using Deep Neural Networks: A Summary of Results.
CoRR, 2018

A New Formulation of The Shortest Path Problem with On-Time Arrival Reliability.
CoRR, 2018

Finding Top-k Optimal Sequenced Routes - Full Version.
CoRR, 2018

Learning to Route with Sparse Trajectory Sets - Extended Version.
CoRR, 2018

Outlier Detection for Multidimensional Time Series Using Deep Neural Networks.
Proceedings of the 19th IEEE International Conference on Mobile Data Management, 2018

aSTEP: Aau's Spatio-TEmporal Data Analytics Platform.
Proceedings of the 19th IEEE International Conference on Mobile Data Management, 2018

Stochastic Shortest Path Finding in Path-Centric Uncertain Road Networks.
Proceedings of the 19th IEEE International Conference on Mobile Data Management, 2018

Finding Top-k Optimal Sequenced Routes.
Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

Learning to Route with Sparse Trajectory Sets.
Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

Distinguishing Trajectories from Different Drivers using Incompletely Labeled Trajectories.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

Correlated Time Series Forecasting using Multi-Task Deep Neural Networks.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017
Enabling time-dependent uncertain eco-weights for road networks.
GeoInformatica, 2017

Assessing the Accuracy Benefits of On-the-Fly Trajectory Selection in Fine-Grained Travel-Time Estimation.
Proceedings of the 18th IEEE International Conference on Mobile Data Management, 2017

2016
Enabling Smart Transportation Systems: A Parallel Spatio-Temporal Database Approach.
IEEE Trans. Computers, 2016

Path Cost Distribution Estimation Using Trajectory Data.
Proc. VLDB Endow., 2016

Finding non-dominated paths in uncertain road networks.
Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016, Burlingame, California, USA, October 31, 2016

Finding Frequently Visited Indoor POIs Using Symbolic Indoor Tracking Data.
Proceedings of the 19th International Conference on Extending Database Technology, 2016

2015
Toward personalized, context-aware routing.
VLDB J., 2015

Discovery of Path Nearby Clusters in Spatial Networks.
IEEE Trans. Knowl. Data Eng., 2015

Network-Matched Trajectory-Based Moving-Object Database: Models and Applications.
IEEE Trans. Intell. Transp. Syst., 2015

EcoMark 2.0: empowering eco-routing with vehicular environmental models and actual vehicle fuel consumption data.
GeoInformatica, 2015

Efficient and Accurate Path Cost Estimation Using Trajectory Data.
CoRR, 2015

Finding top-k local users in geo-tagged social media data.
Proceedings of the 31st IEEE International Conference on Data Engineering, 2015

EcoSky: Reducing vehicular environmental impact through eco-routing.
Proceedings of the 31st IEEE International Conference on Data Engineering, 2015

Personalized route recommendation using big trajectory data.
Proceedings of the 31st IEEE International Conference on Data Engineering, 2015

2014
Using Incomplete Information for Complete Weight Annotation of Road Networks.
IEEE Trans. Knowl. Data Eng., 2014

Towards Total Traffic Awareness.
SIGMOD Rec., 2014

Integrating non-spatial preferences into spatial location queries.
Proceedings of the Conference on Scientific and Statistical Database Management, 2014

Enabling Time-Dependent Uncertain Eco-Weights For Road Networks.
Proceedings of Workshop on Managing and Mining Enriched Geo-Spatial Data, 2014

Efficient Top-k Spatial Locality Search for Co-located Spatial Web Objects.
Proceedings of the IEEE 15th International Conference on Mobile Data Management, 2014

Stochastic skyline route planning under time-varying uncertainty.
Proceedings of the IEEE 30th International Conference on Data Engineering, Chicago, 2014

2013
Finding Shortest Paths on Terrains by Killing Two Birds with One Stone.
Proc. VLDB Endow., 2013

Travel Cost Inference from Sparse, Spatio-Temporally Correlated Time Series Using Markov Models.
Proc. VLDB Endow., 2013

Using Incomplete Information for Complete Weight Annotation of Road Networks - Extended Version.
CoRR, 2013

MOIR/UOTS: Trip Recommendation with User Oriented Trajectory Search.
Proceedings of the 2013 IEEE 14th International Conference on Mobile Data Management, Milan, Italy, June 3-6, 2013, 2013

Building Accurate 3D Spatial Networks to Enable Next Generation Intelligent Transportation Systems.
Proceedings of the 2013 IEEE 14th International Conference on Mobile Data Management, Milan, Italy, June 3-6, 2013, 2013

EcoTour: Reducing the Environmental Footprint of Vehicles Using Eco-routes.
Proceedings of the 2013 IEEE 14th International Conference on Mobile Data Management, Milan, Italy, June 3-6, 2013, 2013

Towards context-aware search and analysis on social media data.
Proceedings of the Joint 2013 EDBT/ICDT Conferences, 2013

iPark: identifying parking spaces from trajectories.
Proceedings of the Joint 2013 EDBT/ICDT Conferences, 2013

2012
EcoMark: evaluating models of vehicular environmental impact.
Proceedings of the SIGSPATIAL 2012 International Conference on Advances in Geographic Information Systems (formerly known as GIS), 2012

2011
Scalable spatio-temporal knowledge harvesting.
Proceedings of the 20th International Conference on World Wide Web, 2011

Efficient Approximate Similarity Search Using Random Projection Learning.
Proceedings of the Web-Age Information Management - 12th International Conference, 2011

Spatio-temporal joins on symbolic indoor tracking data.
Proceedings of the 27th International Conference on Data Engineering, 2011

Harvesting facts from textual web sources by constrained label propagation.
Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

2010
Indoor - A New Data Management Frontier.
IEEE Data Eng. Bull., 2010

XML Structural Similarity Search Using MapReduce.
Proceedings of the Web-Age Information Management, 11th International Conference, 2010

Probabilistic threshold k nearest neighbor queries over moving objects in symbolic indoor space.
Proceedings of the EDBT 2010, 2010

2009
Indexing the Trajectories of Moving Objects in Symbolic Indoor Space.
Proceedings of the Advances in Spatial and Temporal Databases, 2009

Graph Model Based Indoor Tracking.
Proceedings of the MDM 2009, 2009

TRUSTER: TRajectory Data Processing on ClUSTERs.
Proceedings of the Database Systems for Advanced Applications, 2009

Scalable continuous range monitoring of moving objects in symbolic indoor space.
Proceedings of the 18th ACM Conference on Information and Knowledge Management, 2009

Query processing of massive trajectory data based on mapreduce.
Proceedings of the First International CIKM Workshop on Cloud Data Management, 2009

2008
Using Wide Table to manage web data: a survey.
Frontiers Comput. Sci. China, 2008


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