Skip to main content

Implementation of various EDL loss functions

Project description

EDL Losses for CSI-VAE

A research library implementing some Evidential Deep Learning (EDL) loss functions available in the literature.

Currently the losses from the following papers are implemented:

Getting Started

Prerequisites

  • Python 3.13+

Installation

Clone the parent repository and navigate to this module:

git clone <repo-url>
cd csi_vae/edl_losses
pip install -r requirements.txt

Usage

from losses import edl_loss

# Example usage
loss = edl_loss(predictions, targets, epoch)
loss.backward()

License

MIT. See LICENSE.

Author

Luca Cotti (luca.cotti@unibs.it)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

edl_losses-0.2.0.tar.gz (4.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

edl_losses-0.2.0-py3-none-any.whl (6.0 kB view details)

Uploaded Python 3

File details

Details for the file edl_losses-0.2.0.tar.gz.

File metadata

  • Download URL: edl_losses-0.2.0.tar.gz
  • Upload date:
  • Size: 4.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.7 {"installer":{"name":"uv","version":"0.11.7","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for edl_losses-0.2.0.tar.gz
Algorithm Hash digest
SHA256 2ae695dab76f929ff9e893469c0df7fa7f25aea2520ea66c185dbf06e8f6539f
MD5 ae1891a58ca1b6dc117b44cb1d300b3e
BLAKE2b-256 202e603201a2f884df0f582917ee32580d67dbfbbb1d04a13b082a3513f7599a

See more details on using hashes here.

File details

Details for the file edl_losses-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: edl_losses-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 6.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.7 {"installer":{"name":"uv","version":"0.11.7","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for edl_losses-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 31ce7f7e8a93151b2684ebb18a493cdae857b73942e009453b10290c2a5d932b
MD5 a2eab0879dc22e33a0eea500752f892e
BLAKE2b-256 3f6e80d1fcc474b956c2aa5a95853f7fcfaadadd7feee6aaf758b7e41e532731

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page