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Code for 'Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification'

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Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification

This repository is the official implementation of [Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification].

Requirements

To install requirements:

pip install -r requirements.txt

Evaluation

To evaluate my model on CUB for the unbalanced setting, run:

python bavardage.py --shot 1/5 --T_km 10 --T_vb 4 --clp 5

For the balanced setting, run:

python bavardage.py --shot 1/5 --T_km 10 --T_vb 4 --clp 5 --balanced

Pre-trained Models

We provide a WRN model pretrained on CUB in ./checkpoints

Results

Our model achieves the following performance on :

CUB

Model name 1 shot (unbalanced) 5 shot (unbalanced) 1 shot (balanced) 5 shot (balanced)
BAVARDAGE 82.00% 90.67% 85.64% 91.42%

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Code for 'Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification'

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