squarefk
opened
Aug 24, 2020
#
differentiable-programming
Here are 41 public repositories matching this topic...
marcrasi
commented
Nov 10, 2020
It would be nice to change the code in https://github.com/tensorflow/swift/blob/master/docs/site/tutorials/Swift_autodiff_sharp_edges.ipynb into executable code, with some example invocations, so that we can easily verify that it still works every time we release a new toolchain.
10 differentiable physical simulators built with Taichi differentiable programming (DiffTaichi, ICLR 2020)
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Updated
Sep 24, 2020
serenabooth
commented
Oct 30, 2019
Ankit Shah and I are trying to use Gen to support a project and would love the addition of a dirichlet distribution
texasmichelle
commented
Sep 9, 2020
Model summary formatting is rudimentary and could be improved so that tabs align. Potentially use some ideas from swift-benchmark.
torchbearer: A model fitting library for PyTorch
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Updated
Feb 17, 2020 - Python
Shape-Safe Symbolic Differentiation with Algebraic Data Types
kotlin
machine-learning
types
functional-programming
computer-algebra
automatic-differentiation
differentiable-programming
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Updated
Nov 11, 2020 - Kotlin
⟨Leibniz-Grassmann-Clifford⟩ differential geometric algebra / multivector simplicial complex
topology
algebra
math
computer-algebra
linear-algebra
automatic-differentiation
quantum-computing
sparse
quaternion
complex-numbers
computational-geometry
differential-geometry
tensor
lie-groups
tensor-algebra
geometric-algebra
clifford-algebras
differentiable-programming
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Updated
Sep 17, 2020 - Julia
Experimental tensor-typed deep learning
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Updated
Sep 12, 2019 - Scala
L1: Tensor Studio — The playground for tensors
visualization
deep-learning
neural-network
functional-programming
linear-algebra
differentiable-programming
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Updated
Jan 7, 2019 - JavaScript
Differentiable RayTracing in Julia
machine-learning
optimization
julia
ray-tracer
raytracer
gradient-descent
gpu-support
mesh-rendering
differentiable-programming
inverse-rendering
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Updated
Oct 30, 2020 - Julia
High-performance automatic differentiation of LLVM.
c
rust
machine-learning
deep-learning
enzyme
compiler
cpp
simulation
tensorflow
ad
high-performance
llvm
automatic-differentiation
clang
pytorch
scientific-computing
derivative
gradient
hacktoberfest
differentiable-programming
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Updated
Nov 4, 2020 - C++
A differentiable simulator for scientific machine learning (SciML) with N-body problems, including astrophysical and molecular dynamics
automatic-differentiation
molecular-dynamics
molecular-dynamics-simulation
geometric-algorithms
algorithmic-differentiation
differentiable-programming
symbolic-integration
scientific-machine-learning
sciml
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Updated
Nov 3, 2020 - Julia
Julia bindings for the Enzyme automatic differentiator
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Updated
Nov 6, 2020 - Julia
Answer Set & SAT solver for probability distribution-aware model sampling and multi-models optimization using Differentiable Satisfiability. *** Use cases, e.g., probabilistic SAT solving and probabilistic Answer Set Programming.
optimization
artificial-intelligence
constraint-programming
probabilistic-programming
logic-programming
sat-solver
answer-set-programming
satisfiability
differentiable-programming
psat
differentiable-satisfiability
dimacs-cnf
probabilistic-asp
probabilistic-satisfiability
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Updated
Nov 7, 2020 - Scala
Source code for the examples accompanying the paper "Learning convex optimization control policies."
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Updated
Dec 24, 2019 - Jupyter Notebook
A common interface for quadrature and numerical integration for the SciML scientific machine learning organization
integration
automatic-differentiation
quadrature
algorithmic-differentiation
differentiable-programming
scientific-machine-learning
sciml
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Updated
Nov 3, 2020 - Julia
Differentiable Duckietown
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Updated
Jul 27, 2019 - Julia
Evolving graph plotting with differentiable programming on Tensorflow 2
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Updated
Feb 13, 2020 - Jupyter Notebook
Hitchhiker's Guide to Deep Learning for Computational Scientists
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Updated
Nov 26, 2018 - Python
A unified end-to-end learning and control framework that is able to learn a (neural) control objective function, dynamics equation, control policy, or/and optimal trajectory in a control system.
reinforcement-learning
machine-learning-algorithms
motion-planning
dynamical-systems
control-systems
trajectory-optimization
optimal-control
system-identification
imitation-learning
inverse-reinforcement-learning
end-to-end-learning
differentiable-programming
reinforcement-learning-environments
learning-control
pontryagin-maximum-principle
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Updated
Oct 24, 2020 - Python
Deep relational learning through differentiable logic programming.
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Updated
Nov 10, 2020 - Java
srikumarks / df
Code for understanding automatic differentiation.
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Updated
May 9, 2019 - Haskell
Differentiable Tensor Renormalization Group for square Ising
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Updated
Feb 22, 2019 - Julia
learning state-space targets in dynamical systems
machine-learning
continuation
state-space
dynamical-systems
kernel-density-estimation
differentiable-programming
pseudo-arclength-continuation
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Updated
Oct 23, 2020 - Julia
variationally solve hydrogen atom with autograd
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Updated
May 20, 2019 - Python
Differentiable Functional Language
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Updated
May 5, 2020 - Haskell
mirror of Infergo repository
go
golang
machine-learning
automatic-differentiation
inference
artificial-intelligence
algorithmic-differentiation
differentiable-programming
progabilistic-programming
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Updated
Jul 27, 2020 - Go
Various developer materials, like PDFs, notes, derivations, etc. for differential equations and scientific machine learning (SciML)
automatic-differentiation
differential-equations
algorithmic-differentiation
differentiable-programming
scientific-machine-learning
sciml
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Updated
Jun 1, 2020 - Jupyter Notebook
A reproduction and tweaking of Growing Neural Cellular Automata
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Updated
Feb 27, 2020 - Python
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