Skip to main content

tcn package

Project description

This repository contains the experiments done in the work [An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling](https://arxiv.org/abs/1803.01271) by Shaojie Bai, J. Zico Kolter and Vladlen Koltun.

We specifically target a comprehensive set of tasks that have been repeatedly used to compare the effectiveness of different recurrent networks, and evaluate a simple, generic but powerful (purely) convolutional network on the recurrent nets’ home turf.

Experiments are done in PyTorch. If you find this repository helpful, please cite our work:

Project details


Download files

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

Files for astar-tcn, version 0.0.1
Filename, size File type Python version Upload date Hashes
Filename, size astar_tcn-0.0.1-py3-none-any.whl (3.9 kB) File type Wheel Python version 3.6 Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page