Skip to main content

A pip installable version of the lognormal mixture distribution from https://github.com/shchur/ifl-tpp/tree/master/code

Project description

Intensity-Free Learning of Temporal Point Processes

Pip installable version of the pytorch lognormal mixture distribution from the paper "Intensity-Free Learning of Temporal Point Processes", Oleksandr Shchur, Marin Biloš and Stephan Günnemann, ICLR 2020.

Requirements

pytorch>=1.2.0

Cite

Please cite the original author's paper if you use this code in your own work

@article{
    shchur2020intensity,
    title={Intensity-Free Learning of Temporal Point Processes},
    author={Oleksandr Shchur and Marin Bilo\v{s} and Stephan G\"{u}nnemann},
    journal={International Conference on Learning Representations (ICLR)},
    year={2020},
}

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

pytorch_lognormal_mixture-0.0.1.tar.gz (5.1 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file pytorch_lognormal_mixture-0.0.1.tar.gz.

File metadata

File hashes

Hashes for pytorch_lognormal_mixture-0.0.1.tar.gz
Algorithm Hash digest
SHA256 e4b0b184fe094c90f54c325c0bd95450b5664a681d51dc582c80726317f17bec
MD5 4c865a9be5fb61c0e577e4653694a31f
BLAKE2b-256 5f52e703c2d3e47c6dcd5dd8730750165dc9b192e0bc1e866a147a8fb32cdf2a

See more details on using hashes here.

File details

Details for the file pytorch_lognormal_mixture-0.0.1-py3-none-any.whl.

File metadata

File hashes

Hashes for pytorch_lognormal_mixture-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 ab192d069d59c61d8682cc0430a9d4533bbf3ef38fa5c10da5331a3eba32a1c5
MD5 8725741f6518f3a5464fae326fcd38f9
BLAKE2b-256 e7a9895a16cc91e03db7a90112516172faf3c7a9de2f7180c75a5c934d5ae7a2

See more details on using hashes here.

Supported by

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