pytensor
PyTensor allows you to define, optimize, and efficiently evaluate mathematical expressions involving multi-dimensional arrays. (by pymc-devs)
fortuna
A Library for Uncertainty Quantification. (by awslabs)
| pytensor | fortuna | |
|---|---|---|
| 1 | 5 | |
| 570 | 913 | |
| 3.5% | - | |
| 9.8 | 6.3 | |
| 7 days ago | 8 months ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pytensor
Posts with mentions or reviews of pytensor. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-30.
- [D] Programming language for developing computational statistics algorithms
I wouldn't overlook also how many goodies these existing PPLs are coming with. Starting from scratch means that one would have code up all the utilities to assess convergence, chain properties, etc. etc. on their own. And more advanced tricks like auto-differentiations that by themselves are huge perks are also unavailable (goodbye easy ADVI). For example PyMC, now uses Numba and JAX (via Aesara/PyTensor depending on your version), so theoretically (and practically) you can include arbitary PyTensor/JAX code in your model. I use PyMC as an example here, but this extends to most other PPLs too depending on their backends.
fortuna
Posts with mentions or reviews of fortuna. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-04.
- 🚀 AWS launches Fortuna, an open-source library for Uncertainty Quantification
- [P] 🚀 AWS launches Fortuna, an open-source library for Uncertainty Quantification
What is the best end-to-end example showing it? https://github.com/awslabs/fortuna/blob/main/examples/mnist_classification.ipynb ? It would be nice to have some visual explainer, as in https://github.com/aangelopoulos/conformal_classification .
- AWS Fortuna, an open-source library for Uncertainty Quantification
What are some alternatives?
When comparing pytensor and fortuna you can also consider the following projects:
ml_algo_in_depth - ML algorithms in depth
surface_normal_uncertainty - [ICCV 2021 Oral] Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation
gammy - :octopus: Generalized additive models in Python with a Bayesian twist
TrackMania_AI - Racing game AI
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
GradCache - Run Effective Large Batch Contrastive Learning Beyond GPU/TPU Memory Constraint