| Name | Version | Summary | date |
| protes |
0.3.9 |
Method PROTES (PRobabilistic Optimizer with TEnsor Sampling) for derivative-free optimization of the multidimensional arrays and discretized multivariate functions based on the tensor train (TT) format |
2024-10-24 10:20:06 |
| teneva-opti |
0.6.0 |
Collection of various optimization methods, including tensor based, for multivariate functions and multidimensional data arrays |
2024-04-23 13:44:01 |
| teneva-bm |
0.9.0 |
Benchmarks library, based on the package teneva, for testing multivariate approximation and optimization methods |
2024-04-22 12:47:39 |
| fpcross |
0.5.5 |
Solver in the low-rank tensor-train format with cross approximation approach for solution of the multidimensional Fokker-Planck equation |
2023-10-24 15:27:20 |
| teneva |
0.14.8 |
Compact implementation of basic operations in the tensor-train (TT) format, including TT-SVD, TT-ALS, TT-ANOVA, TT-CROSS, TT-truncate for approximation of multidimensional arrays and multivariate functions |
2023-10-17 08:26:02 |
| ttopt |
0.6.2 |
Multivariate function optimizer based on the tensor train approach. |
2023-07-27 20:14:25 |
| teneva-jax |
0.1.1 |
Compact implementation of basic operations in the tensor-train (TT) format with jax framework for approximation, optimization and sampling with multidimensional arrays and multivariate functions |
2023-04-24 20:58:22 |
| teneva-ht-jax |
0.1.2 |
Compact implementation of basic operations in the Hierarchical Tucker (HT) format for approximation and sampling from multidimensional arrays and multivariate functions |
2023-04-21 10:48:27 |
Andrei Chertkov