Publications (73)
Extend Wave Function Collapse to Large-Scale Content Generation
Yuhe Nie, Shaoming Zheng, Zhan Zhuang +1
Wave Function Collapse (WFC) is a widely used tile-based algorithm in procedural content generation, including textures, objects, and scenes. However, the current WFC algorithm and…
Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting
Zheng Dong, Renhe Jiang, Haotian Gao +4
Spatiotemporal time series forecasting plays a key role in a wide range of real-world applications. While significant progress has been made in this area, fully capturing and lever…
Evaluating the Generalization Ability of Spatiotemporal Model in Urban Scenario
Hongjun Wang, Jiyuan Chen, Tong Pan +4
Spatiotemporal neural networks have shown great promise in urban scenarios by effectively capturing temporal and spatial correlations. However, urban environments are constantly ev…
TrafPS: A Shapley-based Visual Analytics Approach to Interpret Traffic
Zezheng Feng, Yifan Jiang, Hongjun Wang +5
Recent achievements in deep learning (DL) have shown its potential for predicting traffic flows. Such predictions are beneficial for understanding the situation and making decision…
Learning to Generate Pseudo Personal Mobility
Peiran Li, Haoran Zhang, Wenjing Li +6
The importance of personal mobility data is widely recognized in various fields. However, the utilization of real personal mobility data raises privacy concerns. Therefore, it is c…
GOF-TTE: Generative Online Federated Learning Framework for Travel Time Estimation
Zhiwen Zhang, Hongjun Wang, Jiyuan Chen +3
Estimating the travel time of a path is an essential topic for intelligent transportation systems. It serves as the foundation for real-world applications, such as traffic monitori…
Metapopulation Graph Neural Networks: Deep Metapopulation Epidemic Modeling with Human Mobility
Qi Cao, Renhe Jiang, Chuang Yang +3
Epidemic prediction is a fundamental task for epidemic control and prevention. Many mechanistic models and deep learning models are built for this task. However, most mechanistic m…
The R2Pub Telescopes for Surveying: An Overview and Performance Evaluation of the System
Xuan Song, Xiaofeng Wang, Jin Zhu +29
The R2Pub telescope, built by the Beijing Planetarium, is a 60 cm equatorial binocular telescope located at the Daocheng site of Yunnan Observatories in China, at an altitude of ab…
Resilience Inference for Supply Chains with Hypergraph Neural Network
Zetian Shen, Hongjun Wang, Jiyuan Chen +1
Supply chains are integral to global economic stability, yet disruptions can swiftly propagate through interconnected networks, resulting in substantial economic impacts. Accurate…
Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting
Jinliang Deng, Feiyang Ye, Du Yin +3
Long-term time series forecasting (LTSF) represents a critical frontier in time series analysis, characterized by extensive input sequences, as opposed to the shorter spans typical…
Properties and Asteroseismological analysis of a new ZZ ceti discovered by TMTS
Jincheng Guo, Yanhui Chen, Xiaofeng Wang +24
Tsinghua university-Ma Huateng Telescope for Survey (TMTS) aims to discover rapidly evolving transients by monitoring the northern sky. The TMTS catalog is cross-matched with the w…
MetaGen: Self-Evolving Roles and Topologies for Multi-Agent LLM Reasoning
Yimeng Wang, Jiaxing Zhao, Hongbin Xie +6
Large language models are increasingly deployed as multi-agent systems, where specialized roles communicate and collaborate through structured interactions to solve complex tasks t…
Event-Aware Multimodal Mobility Nowcasting
Zhaonan Wang, Renhe Jiang, Hao Xue +3
As a decisive part in the success of Mobility-as-a-Service (MaaS), spatio-temporal predictive modeling for crowd movements is a challenging task particularly considering scenarios…
Cochain: Balancing Insufficient and Excessive Collaboration in LLM Agent Workflows
Jiaxing Zhao, Hongbin Xie, Yuzhen Lei +6
Large Language Models (LLMs) have demonstrated impressive performance in executing complex reasoning tasks. Chain-of-thought effectively enhances reasoning capabilities by unlockin…
Route to Time and Time to Route: Travel Time Estimation from Sparse Trajectories
Zhiwen Zhang, Hongjun Wang, Zipei Fan +3
Due to the rapid development of Internet of Things (IoT) technologies, many online web apps (e.g., Google Map and Uber) estimate the travel time of trajectory data collected by mob…
A Multi-view Multi-task Learning Framework for Multi-variate Time Series Forecasting
Jinliang Deng, Xiusi Chen, Renhe Jiang +2
Multi-variate time series (MTS) data is a ubiquitous class of data abstraction in the real world. Any instance of MTS is generated from a hybrid dynamical system and their specific…
An open GPS trajectory dataset and benchmark for travel mode detection
Jinyu Chen, Haoran Zhang, Xuan Song +1
Travel mode detection has been a hot topic in the field of GPS trajectory-related processing. Former scholars have developed many mathematical methods to improve the accuracy of de…
A Phone-based Distributed Ambient Temperature Measurement System with An Efficient Label-free Automated Training Strategy
Dayin Chen, Xiaodan Shi, Haoran Zhang +4
Enhancing the energy efficiency of buildings significantly relies on monitoring indoor ambient temperature. The potential limitations of conventional temperature measurement techni…
Not All Degradations Are Equal: A Targeted Feature Denoising Framework for Generalizable Image Super-Resolution
Hongjun Wang, Jiyuan Chen, Zhengwei Yin +2
Generalizable Image Super-Resolution aims to enhance model generalization capabilities under unknown degradations. To achieve this goal, the models are expected to focus only on im…
STAEformer: Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting
Hangchen Liu, Zheng Dong, Renhe Jiang +4
With the rapid development of the Intelligent Transportation System (ITS), accurate traffic forecasting has emerged as a critical challenge. The key bottleneck lies in capturing th…
Compositional Model Checking of Consensus Protocols Specified in TLA+ via Interaction-Preserving Abstraction
Xiaosong Gu, Wei Cao, Yicong Zhu +3
Consensus protocols are widely used in building reliable distributed software systems and its correctness is of vital importance. TLA+ is a lightweight formal specification languag…
Atomic-Scale Visualization of Chiral Charge Density Wave States and Their Reversible Transition
Xuan Song, Liwei Liu, Yaoyao Chen +13
Chirality is essential for various amazing phenomena in life and matter. However,chirality and its switching in electronic superlattices, such as charge density wave(CDW) arrays, r…
Unveiling the Inflexibility of Adaptive Embedding in Traffic Forecasting
Hongjun Wang, Jiyuan Chen, Lingyu Zhang +2
Spatiotemporal Graph Neural Networks (ST-GNNs) and Transformers have shown significant promise in traffic forecasting by effectively modeling temporal and spatial correlations. How…
Curriculum Reinforcement Learning via Morphology-Environment Co-Evolution
Shuang Ao, Tianyi Zhou, Guodong Long +2
Throughout long history, natural species have learned to survive by evolving their physical structures adaptive to the environment changes. In contrast, current reinforcement learn…
Benchmarking Neural Decoding Backbones towards Enhanced On-edge iBCI Applications
Zhou Zhou, Guohang He, Zheng Zhang +5
Traditional invasive Brain-Computer Interfaces (iBCIs) typically depend on neural decoding processes conducted on workstations within laboratory settings, which prevents their ever…
HarmoQ: Harmonized Post-Training Quantization for High-Fidelity Image
Hongjun Wang, Jiyuan Chen, Xuan Song +1
Post-training quantization offers an efficient pathway to deploy super-resolution models, yet existing methods treat weight and activation quantization independently, missing their…
Universal Design Methodology for Printable Microstructural Materials via a New Deep Generative Learning Model: Application to a Piezocomposite
Mohammad Saber Hashemi, Khiem Nguyen, Levi Kirby +2
We devised a general heterogeneous microstructural design methodology applied to a specific material system, elasto-electro-active piezoelectric ceramic embedded plastics, which ha…
Effective Metagraph-based Life Pattern Clustering with Big Human Mobility Data
Wenjing Li, Haoran Zhang, Jinyu Chen +5
Life pattern clustering is essential for abstracting the groups' characteristics of daily mobility patterns and activity regularity. Based on millions of GPS records, this paper pr…
Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting
Jinliang Deng, Xiusi Chen, Renhe Jiang +4
Multivariate time-series (MTS) forecasting is a paramount and fundamental problem in many real-world applications. The core issue in MTS forecasting is how to effectively model com…
Direct identification of Mott Hubbard band pattern beyond charge density wave superlattice in monolayer 1T-NbSe2
Liwei Liu, Han Yang, Yuting Huang +15
Understanding Mott insulators and charge density waves (CDW) is critical for both fundamental physics and future device applications. However, the relationship between these two ph…
Continuous Domain Generalization
Zekun Cai, Yiheng Yao, Guangji Bai +4
Real-world data distributions often shift continuously across multiple latent factors such as time, geography, and socioeconomic contexts. However, existing domain generalization a…
Domain Adversarial Graph Convolutional Network Based on RSSI and Crowdsensing for Indoor Localization
Mingxin Zhang, Zipei Fan, Ryosuke Shibasaki +1
In recent years, the use of WiFi fingerprints for indoor positioning has grown in popularity, largely due to the widespread availability of WiFi and the proliferation of mobile com…
Learning Gaussian Mixture Representations for Tensor Time Series Forecasting
Jiewen Deng, Jinliang Deng, Renhe Jiang +1
Tensor time series (TTS) data, a generalization of one-dimensional time series on a high-dimensional space, is ubiquitous in real-world scenarios, especially in monitoring systems…
Sunspots rotation and magnetic transients associated with flares in NOAA AR 11429
Jianchuan Zheng, Zhiliang Yang, Jianpeng Guo +4
We analyze sunspots rotation and magnetic transients in NOAA AR 11429 during two X-class (X5.4 and X1.3) flares using the data from the Helioseismic and Magnetic Imager on board th…
Hyper-Relational Knowledge Graph Neural Network for Next POI
Jixiao Zhang, Yongkang Li, Ruotong Zou +3
With the advancement of mobile technology, Point of Interest (POI) recommendation systems in Location-based Social Networks (LBSN) have brought numerous benefits to both users and…
VLUC: An Empirical Benchmark for Video-Like Urban Computing on Citywide Crowd and Traffic Prediction
Renhe Jiang, Zekun Cai, Zhaonan Wang +5
Nowadays, massive urban human mobility data are being generated from mobile phones, car navigation systems, and traffic sensors. Predicting the density and flow of the crowd or tra…
Small World Model for scaling up prediction result based on SEIR model
Guixu Lin, Defan Feng, Peiran Li +3
Data-driven epidemic simulation helps better policymaking. Compared with macro-scale simulations driven by statistical data, individual-level GPS data can afford finer and spatiali…
Robust Traffic Forecasting against Spatial Shift over Years
Hongjun Wang, Jiyuan Chen, Tong Pan +4
Recent advancements in Spatiotemporal Graph Neural Networks (ST-GNNs) and Transformers have demonstrated promising potential for traffic forecasting by effectively capturing both t…
Manifold-Aware Temporal Domain Generalization for Large Language Models
Yiheng Yao, Zekun Cai, Xinyuan Song +4
Temporal distribution shifts are pervasive in real-world deployments of Large Language Models (LLMs), where data evolves continuously over time. While Temporal Domain Generalizatio…
Multi-Modality Spatio-Temporal Forecasting via Self-Supervised Learning
Jiewen Deng, Renhe Jiang, Jiaqi Zhang +1
Multi-modality spatio-temporal (MoST) data extends spatio-temporal (ST) data by incorporating multiple modalities, which is prevalent in monitoring systems, encompassing diverse tr…
ST-ExpertNet: A Deep Expert Framework for Traffic Prediction
Hongjun Wang, Jiyuan Chen, Zipei Fan +3
Recently, forecasting the crowd flows has become an important research topic, and plentiful technologies have achieved good performances. As we all know, the flow at a citywide lev…
Visual Graph Mining
Quanshi Zhang, Xuan Song, Ryosuke Shibasaki
In this study, we formulate the concept of "mining maximal-size frequent subgraphs" in the challenging domain of visual data (images and videos). In general, visual knowledge can u…
Indexing Metric Spaces for Exact Similarity Search
Lu Chen, Yunjun Gao, Xuan Song +4
With the continued digitization of societal processes, we are seeing an explosion in available data. This is referred to as big data. In a research setting, three aspects of the da…
MegaCRN: Meta-Graph Convolutional Recurrent Network for Spatio-Temporal Modeling
Renhe Jiang, Zhaonan Wang, Jiawei Yong +6
Spatio-temporal modeling as a canonical task of multivariate time series forecasting has been a significant research topic in AI community. To address the underlying heterogeneity…
Enhancing Spatio-temporal Quantile Forecasting with Curriculum Learning: Lessons Learned
Du Yin, Jinliang Deng, Shuang Ao +6
Training models on spatio-temporal (ST) data poses an open problem due to the complicated and diverse nature of the data itself, and it is challenging to ensure the model's perform…
Accelerating Flood Warnings by 10 Hours: The Power of River Network Topology in AI-enhanced Flood Forecasting
Hongjun Wang, Jiyuan Chen, Yinqiang Zheng +1
Climate change-driven floods demand advanced forecasting models, yet Graph Neural Networks (GNNs) underutilize river network topology due to tree-like structures causing over-squas…
STGformer: Efficient Spatiotemporal Graph Transformer for Traffic Forecasting
Hongjun Wang, Jiyuan Chen, Tong Pan +4
Traffic forecasting is a cornerstone of smart city management, enabling efficient resource allocation and transportation planning. Deep learning, with its ability to capture comple…
Spatio-Temporal Meta-Graph Learning for Traffic Forecasting
Renhe Jiang, Zhaonan Wang, Jiawei Yong +6
Traffic forecasting as a canonical task of multivariate time series forecasting has been a significant research topic in AI community. To address the spatio-temporal heterogeneity…
Multitask Weakly Supervised Learning for Origin Destination Travel Time Estimation
Hongjun Wang, Zhiwen Zhang, Zipei Fan +4
Travel time estimation from GPS trips is of great importance to order duration, ridesharing, taxi dispatching, etc. However, the dense trajectory is not always available due to the…
Online Trajectory Prediction for Metropolitan Scale Mobility Digital Twin
Zipei Fan, Xiaojie Yang, Wei Yuan +4
Knowing "what is happening" and "what will happen" of the mobility in a city is the building block of a data-driven smart city system. In recent years, mobility digital twin that m…
MSCoRe: A Benchmark for Multi-Stage Collaborative Reasoning in LLM Agents
Yuzhen Lei, Hongbin Xie, Jiaxing Zhao +2
Large Language Models (LLMs) have excelled in question-answering (QA) tasks within single domains. However, their reasoning and coordination capabilities in complex, multi-stage sc…
Mobsimilarity: Vector Graph Optimization for Mobility Tableau Comparison
Yuhao Yao, Haoran Zhang, Jinyu Chen +4
Human mobility similarity comparison plays a critical role in mobility estimation/prediction model evaluation, mobility clustering and mobility matching, which exerts an enormous i…
TraceTrans: Translation and Spatial Tracing for Surgical Prediction
Xiyu Luo, Haodong Li, Xinxing Cheng +4
Image-to-image translation models have achieved notable success in converting images across visual domains and are increasingly used for medical tasks such as predicting post-opera…
Easy Begun is Half Done: Spatial-Temporal Graph Modeling with ST-Curriculum Dropout
Hongjun Wang, Jiyuan Chen, Tong Pan +7
Spatial-temporal (ST) graph modeling, such as traffic speed forecasting and taxi demand prediction, is an important task in deep learning area. However, for the nodes in graph, the…
Differentiable Projection for Constrained Deep Learning
Dou Huang, Haoran Zhang, Xuan Song +1
Deep neural networks (DNNs) have achieved extraordinary performance in solving different tasks in various fields. However, the conventional DNN model is steadily approaching the gr…
Towards Efficient and Evidence-grounded Mobility Prediction with LLM-Driven Agent
Linyao Chen, Qinlao Zhao, Zechen Li +7
Individual-level mobility prediction is central to urban simulation, transportation planning, and policy analysis. Supervised sequence models achieve strong accuracy but require ta…
MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation
Zekun Cai, Renhe Jiang, Xinyu Yang +5
Urban time series data forecasting featuring significant contributions to sustainable development is widely studied as an essential task of the smart city. However, with the dramat…
Adaptive Policy Learning for Offline-to-Online Reinforcement Learning
Han Zheng, Xufang Luo, Pengfei Wei +3
Conventional reinforcement learning (RL) needs an environment to collect fresh data, which is impractical when online interactions are costly. Offline RL provides an alternative so…
The first low-mass eclipsing binary within the fully convective zone from TMTS
Cheng Liu, Xiaofeng Wang, Xiaobing Zhang +17
We present a comprehensive photometric and spectroscopic analysis of the short-period (5.32 hours) and low-mass eclipsing binary TMTSJ0803 discovered by Tsinghua-Ma Huateng T…
Variable white dwarfs in TMTS: Asteroseismological analysis of a ZZ Ceti star, TMTS J17184064+2524314
Jincheng Guo, Yanhui Chen, Yonghui Yang +24
The Tsinghua University-Ma Huateng Telescope for Survey (TMTS) has been constantly monitoring the northern sky since 2020 in search of rapidly variable stars. To find variable whit…
A Knowledge-Guided Cross-Modal Feature Fusion Model for Local Traffic Demand Prediction
Lingyu Zhang, Pengfei Xu, Guobin Wu +4
Traffic demand prediction plays a critical role in intelligent transportation systems. Existing traffic prediction models primarily rely on temporal traffic data, with limited effo…
Worldwide wildfire spreading and its severity described by the SIR model
Tong Pan, Hongjun Wang, Jiyuan Chen +1
Global wildfire spreading dynamics and severity are analyzed using the susceptible-infected-recovered (SIR) compartment model. We use the novel FireTracks (FT) Scientific Dataset c…
LAMOST J2043+3413 -- a Fast Disk Precession SW Sextans Candidate in Period Gap
Xin Li, Xiaofeng Wang, Jiren Liu +5
We present follow-up photometric observations and time-series analysis of a nova-like, SW Sextans-type, cataclysmic variable (CV) candidate, LAMOST J204305.95+341340.6 (here after…
DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction
Renhe Jiang, Du Yin, Zhaonan Wang +7
Nowadays, with the rapid development of IoT (Internet of Things) and CPS (Cyber-Physical Systems) technologies, big spatiotemporal data are being generated from mobile phones, car…
Learning to Balance: Diverse Normalization for Cloth-Changing Person Re-Identification
Hongjun Wang, Jiyuan Chen, Zhengwei Yin +2
Cloth-Changing Person Re-Identification (CC-ReID) involves recognizing individuals in images regardless of clothing status. In this paper, we empirically and experimentally demonst…
Causal-Based Supervision of Attention in Graph Neural Network: A Better and Simpler Choice towards Powerful Attention
Hongjun Wang, Jiyuan Chen, Lun Du +3
Recent years have witnessed the great potential of attention mechanism in graph representation learning. However, while variants of attention-based GNNs are setting new benchmarks…
Layer sliding and twisting induced electronic transitions in correlated magnetic 1T-NbSe2 bilayers
Jiaqi Dai, Jingsi Qiao, Cong Wang +9
Correlated two-dimensional (2D) layers, like 1T-phases of TaS2, TaSe2 and NbSe2, exhibit rich tunability through varying interlayer couplings, which promotes the understanding of e…
TrafPS: A Visual Analysis System Interpreting Traffic Prediction in Shapley
Yifan Jiang, Zezheng Feng, Hongjun Wang +2
In recent years, deep learning approaches have been proved good performance in traffic flow prediction, many complex models have been proposed to make traffic flow prediction more…
Continuous Temporal Domain Generalization
Zekun Cai, Guangji Bai, Renhe Jiang +2
Temporal Domain Generalization (TDG) addresses the challenge of training predictive models under temporally varying data distributions. Traditional TDG approaches typically focus o…
EpiMob: Interactive Visual Analytics of Citywide Human Mobility Restrictions for Epidemic Control
Chuang Yang, Zhiwen Zhang, Zipei Fan +4
The outbreak of coronavirus disease (COVID-19) has swept across more than 180 countries and territories since late January 2020. As a worldwide emergency response, governments have…
Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting
Haotian Gao, Renhe Jiang, Zheng Dong +3
Spatiotemporal forecasting techniques are significant for various domains such as transportation, energy, and weather. Accurate prediction of spatiotemporal series remains challeng…
Adaptor: Advancing Assistive Teleoperation with Few-Shot Learning and Cross-Operator Generalization
Yu Liu, Yihang Yin, Tianlv Huang +8
Assistive teleoperation enhances efficiency via shared control, yet inter-operator variability, stemming from diverse habits and expertise, induces highly heterogeneous trajectory…
Rethinking Video Token Compression with a Global Codebook: Learning Once, Compressing Everywhere
Jiayang He, Tianling Xu, Diancheng Kang +4
Video large language models (Video-LLMs) represent videos as dense sequences of visual tokens, whose length grows with the temporal and spatial extent of the input. These tokens of…