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Found 3 papers, 1 papers with code
Motif-based Graph Representation Learning with Application to Chemical Molecules
MCM builds a motif vocabulary in an unsupervised way and deploys a novel motif convolution operation to extract the local structural context of individual nodes, which is then used to learn higher-level node representations via multilayer perceptron and/or message passing in graph neural networks.
Learning Efficient Object Detection Models with Knowledge Distillation
In this work, we propose a new framework to learn compact and fast ob- ject detection networks with improved accuracy using knowledge distillation [20] and hint learning [34].
Object-centric Sampling for Fine-grained Image Classification
In contrast, this paper proposes an \emph{object-centric sampling} (OCS) scheme that samples image windows based on the object location information.
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