research
∙
08/31/2023
BenchTemp: A General Benchmark for Evaluating Temporal Graph Neural Networks
To handle graphs in which features or connectivities are evolving over t...
share
research
∙
08/24/2023
Unified Data Management and Comprehensive Performance Evaluation for Urban Spatial-Temporal Prediction [Experiment, Analysis Benchmark]
The field of urban spatial-temporal prediction is advancing rapidly with...
research
∙
04/27/2023
Towards Efficient and Comprehensive Urban Spatial-Temporal Prediction: A Unified Library and Performance Benchmark
As deep learning technology advances and more urban spatial-temporal dat...
research
∙
04/17/2023
Two-stage MR Image Segmentation Method for Brain Tumors based on Attention Mechanism
Multimodal magnetic resonance imaging (MRI) can reveal different pattern...
research
∙
04/06/2023
GA-HQS: MRI reconstruction via a generically accelerated unfolding approach
Deep unfolding networks (DUNs) are the foremost methods in the realm of ...
research
∙
02/22/2023
BUAA_BIGSCity: Spatial-Temporal Graph Neural Network for Wind Power Forecasting in Baidu KDD CUP 2022
In this technical report, we present our solution for the Baidu KDD Cup ...
research
∙
01/19/2023
PDFormer: Propagation Delay-aware Dynamic Long-range Transformer for Traffic Flow Prediction
As a core technology of Intelligent Transportation System, traffic flow ...
research
∙
01/16/2023
Continuous Trajectory Generation Based on Two-Stage GAN
Simulating the human mobility and generating large-scale trajectories ar...
research
∙
11/17/2022
Self-supervised Trajectory Representation Learning with Temporal Regularities and Travel Semantics
Trajectory Representation Learning (TRL) is a powerful tool for spatial-...
research
∙
09/01/2022
STDEN: Towards Physics-Guided Neural Networks for Traffic Flow Prediction
High-performance traffic flow prediction model designing, a core technol...
research
∙
07/29/2022
Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates
Vertical federated learning (VFL) is an emerging paradigm that allows di...
research
∙
06/12/2022
Stochastic Gradient Descent without Full Data Shuffle
Stochastic gradient descent (SGD) is the cornerstone of modern machine l...
research
∙
05/25/2022
BRIGHT – Graph Neural Networks in Real-Time Fraud Detection
Detecting fraudulent transactions is an essential component to control r...
research
∙
12/26/2021
Efficient Diversity-Driven Ensemble for Deep Neural Networks
The ensemble of deep neural networks has been shown, both theoretically ...
research
∙
05/17/2021
Towards Demystifying Serverless Machine Learning Training
The appeal of serverless (FaaS) has triggered a growing interest on how ...
research
∙
07/03/2019
An Experimental Evaluation of Large Scale GBDT Systems
Gradient boosting decision tree (GBDT) is a widely-used machine learning...
research
∙
11/06/2018
