
# Packed-Ensembles trained on ImageNet-1k

## How to use

Download [TorchUncertainty](https://torch-uncertainty.github.io/) to use this model.

## License

These weights are provided under the Apache 2.0 license.

## Citation

If you find these weights interesting, please consider citing our [paper](https://arxiv.org/abs/2210.09184):

```text
@inproceedings{laurent2023packed,
    title={Packed-Ensembles for Efficient Uncertainty Estimation},
    author={Laurent, Olivier and Lafage, Adrien and Tartaglione, Enzo and Daniel, Geoffrey and Martinez, Jean-Marc and Bursuc, Andrei and Franchi, Gianni},
    booktitle={ICLR},
    year={2023}
}
```

{"license": "apache-2.0", "tags": ["vision", "classification", "uncertainty"], "datasets": ["imagenet-1k"]}
vision classification uncertainty dataset:imagenet-1k arxiv:2210.09184 license:apache-2.0 region:us
TAGS
#vision #classification #uncertainty #dataset-imagenet-1k #arxiv-2210.09184 #license-apache-2.0 #region-us 


# Packed-Ensembles trained on ImageNet-1k

## How to use

Download TorchUncertainty to use this model.

## License

These weights are provided under the Apache 2.0 license.

If you find these weights interesting, please consider citing our paper:



# Packed-Ensembles trained on ImageNet-1k ## How to use

Download TorchUncertainty to use this model. ## License

These weights are provided under the Apache 2.0 license.

If you find these weights interesting, please consider citing our paper:
TAGS
#vision #classification #uncertainty #dataset-imagenet-1k #arxiv-2210.09184 #license-apache-2.0 #region-us 
 # Packed-Ensembles trained on ImageNet-1k ## How to use

Download TorchUncertainty to use this model. ## License

These weights are provided under the Apache 2.0 license.

If you find these weights interesting, please consider citing our paper: