3 citations · 5 across the 7 of their papers we have counts for
4 papers · 1 filter
Inferring Prototypes for Multi-Label Few-Shot Image Classification with Word Vector Guided Attention
Kun Yan, Chenbin Zhang, Jun Hou +4
Multi-label few-shot image classification (ML-FSIC) is the task of assigning descriptive labels to previously unseen images, based on a small number of training examples. A key fea…
CETransformer: Casual Effect Estimation via Transformer Based Representation Learning
Zhenyu Guo, Shuai Zheng, Zhizhe Liu +2
Treatment effect estimation, which refers to the estimation of causal effects and aims to measure the strength of the causal relationship, is of great importance in many fields but…
Aligning Visual Prototypes with BERT Embeddings for Few-Shot Learning
Kun Yan, Zied Bouraoui, Ping Wang +2
Few-shot learning (FSL) is the task of learning to recognize previously unseen categories of images from a small number of training examples. This is a challenging task, as the ava…
Few-shot Image Classification with Multi-Facet Prototypes
Kun Yan, Zied Bouraoui, Ping Wang +2
The aim of few-shot learning (FSL) is to learn how to recognize image categories from a small number of training examples. A central challenge is that the available training exampl…