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04/28/2023
Deep Graph Reprogramming
In this paper, we explore a novel model reusing task tailored for graph ...
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07/24/2022
Learning Graph Neural Networks for Image Style Transfer
State-of-the-art parametric and non-parametric style transfer approaches...
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09/27/2021
Meta-Aggregator: Learning to Aggregate for 1-bit Graph Neural Networks
In this paper, we study a novel meta aggregation scheme towards binarizi...
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06/07/2021
Learning Dynamics via Graph Neural Networks for Human Pose Estimation and Tracking
Multi-person pose estimation and tracking serve as crucial steps for vid...
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04/14/2021
VOLDOR: Visual Odometry from Log-logistic Dense Optical flow Residuals
We propose a dense indirect visual odometry method taking as input exter...
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01/10/2021
SPAGAN: Shortest Path Graph Attention Network
Graph convolutional networks (GCN) have recently demonstrated their pote...
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12/10/2020
Overcoming Catastrophic Forgetting in Graph Neural Networks
Catastrophic forgetting refers to the tendency that a neural network "fo...
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10/14/2020
Learning Propagation Rules for Attribution Map Generation
Prior gradient-based attribution-map methods rely on handcrafted propaga...
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10/12/2020
Factorizable Graph Convolutional Networks
Graphs have been widely adopted to denote structural connections between...
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03/23/2020
Distillating Knowledge from Graph Convolutional Networks
Existing knowledge distillation methods focus on convolutional neural ne...
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03/23/2020
Distilling Knowledge from Graph Convolutional Networks
Existing knowledge distillation methods focus on convolutional neural ne...
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11/12/2016
Dual Teaching: A Practical Semi-supervised Wrapper Method
Semi-supervised wrapper methods are concerned with building effective su...
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02/18/2016
