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  1. ad-kernels ad-kernels Public

    Code for the paper "Algorithmic Differentiation for Automatized Modelling of Machine Learned Force Fields"

    Jupyter Notebook 12 1

  2. DifferentiableDFTK DifferentiableDFTK Public

    Automatic differentiation for density functional theory in Julia.

    Julia 6

  3. sdf_jax sdf_jax Public

    Utilities for neural signed distance fields in JAX.

    Jupyter Notebook 4

  4. JuliaMolSim/DFTK.jl JuliaMolSim/DFTK.jl Public

    Density-functional toolkit

    Julia 446 89

  5. visualizing jaxprs visualizing jaxprs
    1
    import jax
    2
    from jax import core
    3
    from graphviz import Digraph
    4
    import itertools
    5
    
                  
  6. Kernel regression in dex-lang Kernel regression in dex-lang
    1
    import plot
    2
    
                  
    3
    -- Conjugate gradients solver
    4
    def solve (mat:m=>m=>Float) (b:m=>Float) : m=>Float =
    5
      x0 = for i:m. 0.0