Differentiable programming
Differentiable programming is a programming paradigm in which a numeric computer program can be differentiated throughout via automatic differentiation. This allows for gradient-based optimization of parameters in the program, often via gradient descent, as well as other learning approaches that are based on higher order derivative information. Differentiable programming has found use in a wide variety of areas, particularly scientific computing and artificial intelligence. One of the early proposals to adopt such a framework in a systematic fashion to improve upon learning algorithms was made by the Advanced Concepts Team at the European Space Agency in early 2016.
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- enDifferentiable programming is a programming paradigm in which a numeric computer program can be differentiated throughout via automatic differentiation. This allows for gradient-based optimization of parameters in the program, often via gradient descent, as well as other learning approaches that are based on higher order derivative information. Differentiable programming has found use in a wide variety of areas, particularly scientific computing and artificial intelligence. One of the early proposals to adopt such a framework in a systematic fashion to improve upon learning algorithms was made by the Advanced Concepts Team at the European Space Agency in early 2016.
- Has abstract
- enDifferentiable programming is a programming paradigm in which a numeric computer program can be differentiated throughout via automatic differentiation. This allows for gradient-based optimization of parameters in the program, often via gradient descent, as well as other learning approaches that are based on higher order derivative information. Differentiable programming has found use in a wide variety of areas, particularly scientific computing and artificial intelligence. One of the early proposals to adopt such a framework in a systematic fashion to improve upon learning algorithms was made by the Advanced Concepts Team at the European Space Agency in early 2016.
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- Differentiable programming
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- enDifferentiable programming
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- github.com/FluxML/Zygote.jl
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- Advanced Concepts Team
- Artificial intelligence
- AutoGrad (NumPy)
- Automatic differentiation
- Category:Differential calculus
- Category:Programming paradigms
- Compiled
- Compiler optimization
- Data structures
- Deep learning
- Density functional theory
- Differentiable function
- Differentiation (mathematics)
- European Space Agency
- Gradient descent
- Gradient method
- Image processing
- Intermediate representation
- Interpreter (computing)
- Julia (programming language)
- Loop (computing)
- Machine learning
- MXNet
- Operator overloading
- Physics engines
- Probabilistic programming
- Programming paradigm
- PyTorch
- Ray tracing (graphics)
- Recursion
- Robotics
- Scientific computing
- TensorFlow
- Theano (software)
- SameAs
- 9Trtn
- Q63100473
- برمجة تفاضلية
- 可微分编程
- Subject
- Category:Differential calculus
- Category:Programming paradigms
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- Differentiable programming?oldid=1122006098&ns=0
- WikiPageLength
- 9036
- Wikipage page ID
- 59939845
- Wikipage revision ID
- 1122006098
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- Template:Differentiable computing
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