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Found 9 papers, 1 papers with code
Siamese Multiple Attention Temporal Convolution Networks for Human Mobility Signature Identification
Experimental evaluations conducted on two real-world taxi trajectory datasets reveal that our proposed model effectively extracts both local key information and long-term dependencies.
Harnessing Earnings Reports for Stock Predictions: A QLoRA-Enhanced LLM Approach
Accurate stock market predictions following earnings reports are crucial for investors.
Evaluating Modern Approaches in 3D Scene Reconstruction: NeRF vs Gaussian-Based Methods
Exploring the capabilities of Neural Radiance Fields (NeRF) and Gaussian-based methods in the context of 3D scene reconstruction, this study contrasts these modern approaches with traditional Simultaneous Localization and Mapping (SLAM) systems.
3D Scene Reconstruction
Simultaneous Localization and Mapping
FedVAE: Trajectory privacy preserving based on Federated Variational AutoEncoder
The use of trajectory data with abundant spatial-temporal information is pivotal in Intelligent Transport Systems (ITS) and various traffic system tasks.
Time Series Modeling for Heart Rate Prediction: From ARIMA to Transformers
Cardiovascular disease (CVD) is a leading cause of death globally, necessitating precise forecasting models for monitoring vital signs like heart rate, blood pressure, and ECG.
Achieving Resolution-Agnostic DNN-based Image Watermarking: A Novel Perspective of Implicit Neural Representation
Unlike previous methods, our method does not rely on the previous reduction process by directly watermarking the continuous signal instead of image pixels, thus achieving resolution-agnostic watermarking.
Meta Attentive Graph Convolutional Recurrent Network for Traffic Forecasting
Firstly, most approaches are primarily designed to model the local shared patterns, which makes them insufficient to capture the specific patterns associated with each node globally.
DiffTraj: Generating GPS Trajectory with Diffusion Probabilistic Model
In this work, we propose a spatial-temporal diffusion probabilistic model for trajectory generation (DiffTraj).
Traffic Prediction with Transfer Learning: A Mutual Information-based Approach
In modern traffic management, one of the most essential yet challenging tasks is accurately and timely predicting traffic.
