
# Packed-Ensembles ResNet trained on CIFAR-10

## How to use

Download [TorchUncertainty](https://torch-uncertainty.github.io/) - [GitHub](https://github.com/ENSTA-U2IS/torch-uncertainty) to use this model.

## Reference

Consider citing:

**Packed-Ensembles for Efficient Uncertainty Estimation**

* Authors: *Olivier Laurent, Adrien Lafage, Enzo Tartaglione, Geoffrey Daniel, Jean-Marc Martinez, Andrei Bursuc, and Gianni Franchi*
* Paper: [ICLR 2023](https://arxiv.org/abs/2210.09184).

Implementation - [GitHub](https://github.com/ENSTA-U2IS/torch-uncertainty)

## License

These weights are provided under the Apache 2.0 license.

{"license": "apache-2.0", "tags": ["vision", "classification", "uncertainty"], "datasets": ["cifar-10"]}
vision classification uncertainty dataset:cifar-10 arxiv:2210.09184 license:apache-2.0 region:us
TAGS
#vision #classification #uncertainty #dataset-cifar-10 #arxiv-2210.09184 #license-apache-2.0 #region-us 


# Packed-Ensembles ResNet trained on CIFAR-10

## How to use

Download TorchUncertainty - GitHub to use this model.

## Reference

Consider citing:

Packed-Ensembles for Efficient Uncertainty Estimation

* Authors: *Olivier Laurent, Adrien Lafage, Enzo Tartaglione, Geoffrey Daniel, Jean-Marc Martinez, Andrei Bursuc, and Gianni Franchi*
* Paper: ICLR 2023.

Implementation - GitHub

## License

These weights are provided under the Apache 2.0 license.

# Packed-Ensembles ResNet trained on CIFAR-10 ## How to use

Download TorchUncertainty - GitHub to use this model. ## Reference

Consider citing:

Packed-Ensembles for Efficient Uncertainty Estimation

* Authors: *Olivier Laurent, Adrien Lafage, Enzo Tartaglione, Geoffrey Daniel, Jean-Marc Martinez, Andrei Bursuc, and Gianni Franchi*
* Paper: ICLR 2023.

Implementation - GitHub ## License

These weights are provided under the Apache 2.0 license.
TAGS
#vision #classification #uncertainty #dataset-cifar-10 #arxiv-2210.09184 #license-apache-2.0 #region-us 
 # Packed-Ensembles ResNet trained on CIFAR-10 ## How to use

Download TorchUncertainty - GitHub to use this model. ## Reference

Consider citing:

Packed-Ensembles for Efficient Uncertainty Estimation

* Authors: *Olivier Laurent, Adrien Lafage, Enzo Tartaglione, Geoffrey Daniel, Jean-Marc Martinez, Andrei Bursuc, and Gianni Franchi*
* Paper: ICLR 2023.

Implementation - GitHub ## License

These weights are provided under the Apache 2.0 license.
TAGS
#vision #classification #uncertainty #dataset-cifar-10 #arxiv-2210.09184 #license-apache-2.0 #region-us 
# Packed-Ensembles ResNet trained on CIFAR-10## How to use

Download TorchUncertainty - GitHub to use this model.## Reference

Consider citing:

Packed-Ensembles for Efficient Uncertainty Estimation

* Authors: *Olivier Laurent, Adrien Lafage, Enzo Tartaglione, Geoffrey Daniel, Jean-Marc Martinez, Andrei Bursuc, and Gianni Franchi*
* Paper: ICLR 2023.

Implementation - GitHub## License

These weights are provided under the Apache 2.0 license.