102 citations · 322 across the 78 of their papers we have counts for
9 papers · 1 filter
AutoPINN: When AutoML Meets Physics-Informed Neural Networks
Xinle Wu, Dalin Zhang, Miao Zhang +5
Physics-Informed Neural Networks (PINNs) have recently been proposed to solve scientific and engineering problems, where physical laws are introduced into neural networks as prior…
Gaussian Process Latent Variable Modeling for Few-shot Time Series Forecasting
Yunyao Cheng, Chenjuan Guo, Kaixuan Chen +6
Accurate time series forecasting is crucial for optimizing resource allocation, industrial production, and urban management, particularly with the growth of cyber-physical and IoT…
Joint Neural Architecture and Hyperparameter Search for Correlated Time Series Forecasting
Xinle Wu, Dalin Zhang, Miao Zhang +3
Sensors in cyber-physical systems often capture interconnected processes and thus emit correlated time series (CTS), the forecasting of which enables important applications. The ke…
A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis
Yan Zhao, Liwei Deng, Xuanhao Chen +7
The continued digitization of societal processes translates into a proliferation of time series data that cover applications such as fraud detection, intrusion detection, and energ…
RetroGraph: Retrosynthetic Planning with Graph Search
Shufang Xie, Rui Yan, Peng Han +5
Retrosynthetic planning, which aims to find a reaction pathway to synthesize a target molecule, plays an important role in chemistry and drug discovery. This task is usually modele…
Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting--Full Version
Razvan-Gabriel Cirstea, Chenjuan Guo, Bin Yang +3
A variety of real-world applications rely on far future information to make decisions, thus calling for efficient and accurate long sequence multivariate time series forecasting. W…
Weakly-supervised Temporal Path Representation Learning with Contrastive Curriculum Learning -- Extended Version
Sean Bin Yang, Chenjuan Guo, Jilin Hu +3
In step with the digitalization of transportation, we are witnessing a growing range of path-based smart-city applications, e.g., travel-time estimation and travel path ranking. A…
Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection---Extended Version
Tung Kieu, Bin Yang, Chenjuan Guo +4
Time series data occurs widely, and outlier detection is a fundamental problem in data mining, which has numerous applications. Existing autoencoder-based approaches deliver state-…
Towards Spatio-Temporal Aware Traffic Time Series Forecasting--Full Version
Razvan-Gabriel Cirstea, Bin Yang, Chenjuan Guo +2
Traffic time series forecasting is challenging due to complex spatio-temporal dynamics time series from different locations often have distinct patterns; and for the same time seri…