T4transport
Tools for Computational Optimal Transport
Transport theory has seen much success in many fields of statistics and machine learning. We provide a variety of algorithms to compute Wasserstein distance, barycenter, and others. See Peyré and Cuturi (2019) <doi:10.1561/2200000073> for the general exposition to the study of computational optimal transport.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.8 |
rolling linux/jammy R-4.5 | T4transport_0.1.8.tar.gz |
5.1 MiB |
0.1.8 |
rolling linux/noble R-4.5 | T4transport_0.1.8.tar.gz |
5.1 MiB |
0.1.8 |
rolling source/ R- | T4transport_0.1.8.tar.gz |
4.7 MiB |
0.1.8 |
latest linux/jammy R-4.5 | T4transport_0.1.8.tar.gz |
5.1 MiB |
0.1.8 |
latest linux/noble R-4.5 | T4transport_0.1.8.tar.gz |
5.1 MiB |
0.1.8 |
latest source/ R- | T4transport_0.1.8.tar.gz |
4.7 MiB |
0.1.8 |
2026-04-26 source/ R- | T4transport_0.1.8.tar.gz |
4.7 MiB |
0.1.8 |
2026-04-23 source/ R- | T4transport_0.1.8.tar.gz |
4.7 MiB |
0.1.8 |
2026-04-09 windows/windows R-4.5 | T4transport_0.1.8.zip |
5.5 MiB |
0.1.2 |
2025-04-20 source/ R- | T4transport_0.1.2.tar.gz |
4.5 MiB |