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Found 6 papers, 5 papers with code
Graph Out-of-Distribution Generalization with Controllable Data Augmentation
The spurious correlations over hybrid distribution deviation degrade the performance of previous GNN methods and show large instability among different datasets.
Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation
Instead of replacing and retraining the fully connected neural network classifer, Geometer predicts the label of a node by finding the nearest class prototype.
Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer
To address this challenge, cross-city knowledge transfer has shown its promise, where the model learned from data-sufficient cities is leveraged to benefit the learning process of data-scarce cities.
PP-ShiTu: A Practical Lightweight Image Recognition System
In recent years, image recognition applications have developed rapidly.
PP-LCNet: A Lightweight CPU Convolutional Neural Network
We propose a lightweight CPU network based on the MKLDNN acceleration strategy, named PP-LCNet, which improves the performance of lightweight models on multiple tasks.
PP-OCRv2: Bag of Tricks for Ultra Lightweight OCR System
Optical Character Recognition (OCR) systems have been widely used in various of application scenarios.
Optical Character Recognition
Optical Character Recognition (OCR)
