geoopt
Riemannian Adaptive Optimization Methods with pytorch optim (by geoopt)
hyperlib
Library that contains implementations of machine learning components in the hyperbolic space (by nalexai)
geoopt | hyperlib | |
---|---|---|
2 | 5 | |
811 | 123 | |
2.2% | 4.1% | |
4.3 | 2.5 | |
about 2 months ago | 2 months ago | |
Python | Python | |
GNU General Public License v3.0 or later | MIT License |
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.
geoopt
Posts with mentions or reviews of geoopt.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-06-01.
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A walk through of the functions used in "A Universal Model for Hyperbolic, Euclidean and Spherical Geometries" (the κ-Stereographic Model)
Looking at geoopt/manifolds/stereographic/math.py and trying to learn about hyperbolic geometry as I go, wondering if you could add some commentary to the functions. If anyone is in the mood to teach, I am all ears :). I can prompt with some questions, hopefully that will help clarify what is confusing or hard to understand for a newcomer.
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Introducing Hyperlib: Simple Deep learning in Hyperbolic space [project]
Can you expand on this? What other toolkits already exist and how does yours solve the problems you saw in those frameworks? For example, maybe compare with https://github.com/geoopt/geoopt for one?
hyperlib
Posts with mentions or reviews of hyperlib.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-06-15.
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Poincare Embeddings: Embedding technique that works well at low dimensions
Implementation in the HyperLib library with an example: https://github.com/nalexai/hyperlib/blob/main/examples/wordnet_embedding.py
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Hyperbolic Embeddings: Embeddings for Hierarchical Data [R] [P]
Thanks, it should be fixed in the OP now: https://github.com/nalexai/Hyperlib https://medium.com/@nathan_jf/treerep-and-hyperbolic-embeddings-41312c98b264
- Introducing Hyperlib: Simple Deep learning in the Hyperbolic space
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Introducing Hyperlib: Simple Deep learning in Hyperbolic space [project]
Probably slow af on a GPU. It uses 64bit weights: https://github.com/nalexai/hyperlib/blob/c03dce51b42f9b1c211ca209246f69fce7779a00/hyperlib/nn/layers/lin_hyp.py#L21
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Weekly Entering & Transitioning Thread | 30 May 2021 - 06 Jun 2021
Hi all! I've just released a new open-source python library that makes it easy to create the next generation of neural networks in the Hyperbolic space (as opposed to Euclidean). We're calling it Hyperlib.