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06/03/2023
Message-passing selection: Towards interpretable GNNs for graph classification
In this paper, we strive to develop an interpretable GNNs' inference par...
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05/31/2023
Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization
Graph Neural Networks (GNNs) have emerged as a powerful category of lear...
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09/07/2022
A Survey of Neural Trees
Neural networks (NNs) and decision trees (DTs) are both popular models o...
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08/22/2022
ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition
Prototypical part network (ProtoPNet) has drawn wide attention and boost...
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03/22/2022
Meta-attention for ViT-backed Continual Learning
Continual learning is a longstanding research topic due to its crucial r...
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03/07/2022
Knowledge Amalgamation for Object Detection with Transformers
Knowledge amalgamation (KA) is a novel deep model reusing task aiming to...
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12/12/2021
Up to 100x Faster Data-free Knowledge Distillation
Data-free knowledge distillation (DFKD) has recently been attracting inc...
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12/07/2021
Bootstrapping ViTs: Towards Liberating Vision Transformers from Pre-training
Recently, vision Transformers (ViTs) are developing rapidly and starting...
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12/06/2021
A Survey of Deep Learning for Low-Shot Object Detection
Object detection is a fundamental task in computer vision and image proc...
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07/10/2020