# EMMeT

**E**mbedding **M**ixup for **Me**ta-**T**raining (EMMeT), a novel regularization technique that creates new episodic batches through an embedding shuffling and averaging regime.

Weights for the CONV4 and DINO-S models are provided for EMMeT evaluation.

For usage and instructions, please refer to the Github repository: https://github.com/Brikwerk/EMMeT

## Model Date

February 2023
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region:us
TAGS
#region-us 

# EMMeT

Embedding Mixup for Meta-Training (EMMeT), a novel regularization technique that creates new episodic batches through an embedding shuffling and averaging regime.

Weights for the CONV4 and DINO-S models are provided for EMMeT evaluation.

For usage and instructions, please refer to the Github repository: URL

## Model Date

February 2023
# EMMeT

Embedding Mixup for Meta-Training (EMMeT), a novel regularization technique that creates new episodic batches through an embedding shuffling and averaging regime.

Weights for the CONV4 and DINO-S models are provided for EMMeT evaluation.

For usage and instructions, please refer to the Github repository: URL ## Model Date

February 2023
TAGS
#region-us 
 # EMMeT

Embedding Mixup for Meta-Training (EMMeT), a novel regularization technique that creates new episodic batches through an embedding shuffling and averaging regime.

Weights for the CONV4 and DINO-S models are provided for EMMeT evaluation.

For usage and instructions, please refer to the Github repository: URL ## Model Date

February 2023
TAGS
#region-us 
# EMMeT

Embedding Mixup for Meta-Training (EMMeT), a novel regularization technique that creates new episodic batches through an embedding shuffling and averaging regime.

Weights for the CONV4 and DINO-S models are provided for EMMeT evaluation.

For usage and instructions, please refer to the Github repository: URL## Model Date

February 2023