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Top 7 interpretable-ml Open-Source Projects
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Project mention: Potential of the Julia programming language for high energy physics computing | news.ycombinator.com | 2023-12-04> Yes, julia can be called from other languages rather easily
This seems false to me. StaticCompiler.jl [1] puts in their limitations that "GC-tracked allocations and global variables do not work with compile_executable or compile_shlib. This has some interesting consequences, including that all functions within the function you want to compile must either be inlined or return only native types (otherwise Julia would have to allocate a place to put the results, which will fail)." PackageCompiler.jl [2] has the same limitations if I'm not mistaken. So then you have to fall back to distributing the Julia "binary" with a full Julia runtime, which is pretty heavy. There are some packages which do this. For example, PySR [3] does this.
There is some word going around though that there is an even better static compiler in the making, but as long as that one is not publicly available I'd say that Julia cannot easily be called from other languages.
[1]: https://github.com/tshort/StaticCompiler.jl
[2]: https://github.com/JuliaLang/PackageCompiler.jl
[3]: https://github.com/MilesCranmer/PySR
Project mention: Symbolicregression.jl – High-Performance Symbolic Regression in Julia and Python | news.ycombinator.com | 2023-07-15
Project mention: Show HN: Open-Sourcing Google's Lattice Models in PyTorch | news.ycombinator.com | 2023-11-15
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
interpretable-ml related posts
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[D] [R] Research Problem about Weakly Supervised Learning for CT Image Semantic Segmentation
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[D] Off-the-shelf image saliency scoring models?
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Can you interrogate a machine learning model to find out why it gave certain predictions?
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What kind of explainability techniques exist for Reinforcement learning?
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[D] How do you choose which Black-Box Explainability method to use?
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DeepLIFT or other explainable api implementations for JAX (like captum for pytorch)?
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how to extract features from a (CNN) convolutional network having raw data with (XAI) explainable techinques?
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A note from our sponsor - InfluxDB
www.influxdata.com | 6 Jun 2024
Index
What are some of the best open-source interpretable-ml projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | interpret | 6,072 |
| 2 | captum | 4,636 |
| 3 | PySR | 2,017 |
| 4 | SymbolicRegression.jl | 548 |
| 5 | OSDT | 94 |
| 6 | pytorch-lattice | 25 |
| 7 | XAI | 18 |
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