[D] What are some ideas that are hyped up in machine learning research but don't actually get used in industry (and vice versa)?

This page summarizes the projects mentioned and recommended in the original post on /r/MachineLearning
differential-equations Differentialequations neural-differential-equations scientific-ml scientific-ai

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  • NeuralPDE.jl

    Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

    • Did this change at all with the advent of Physics Informed Neural Networks? The Julia language has some really impressive tools for that use case. https://github.com/SciML/NeuralPDE.jl

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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