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Show HN: Brancher – A user-friendly PyTorch module for probabilistic inference
- mooneater 7y agoCan someone comment in this vs Pyro?
- lucaambrogioni 7y agoBrancher is targeted to a wider audience, including people who have only a basic training in machine learning and Python programming. The interface is designed to be as close as possible to the math. The downside is that Brancher is less flexible than Pyro.
- mooneater 7y agoLooks awesome, and thanks for the insight!
- lucaambrogioni 7y agoThank you!
- eli_gottlieb 7y agoHow does this compare to Probabilistic Torch?
- montecarl 7y agoCan anyone comment on how this compares to pymc3?
- lucaambrogioni 7y agoHi. The main difference with PyMC is that Brancher is build on the top of the deep learning library PyTorch. Every deep learning tool that is implemented in PyTorch can be used for constructing deep probabilistic models in Brancher. Also PyMC mostly uses sampling while Brancher is based on variational inference.