StackOverflow Questions for Tag: automatic-differentiation

Hermann

Reputation: 55

How to implement Carleman Matrix in Haskell?

haskellfunctional-programmingnumerical-methodsautomatic-differentiation

Score: 2

Answers: 1

Parisa asghari

Reputation: 9

solving an ODE using neural networks

pytorchneural-networkodeautomatic-differentiation

Score: 1

Answers: 1

Jingyang Wang

Reputation: 323

JAX `custom_vjp` for functions with multiple outputs

pythonjaxautomatic-differentiation

Score: 1

Answers: 1

Jingyang Wang

Reputation: 323

JAX `vjp` fails for vmapped function with `custom_vjp`

pythonvectorizationjaxautomatic-differentiation

Score: 1

Answers: 1

Jingyang Wang

Reputation: 323

JAX `vjp` does not recognize cotangent argument with `custom_vjp`

pythonfunctionjaxautomatic-differentiation

Score: 1

Answers: 1

Mahdi

Reputation: 11

Failing to return gradients

pythongradientjaxautomatic-differentiation

Score: 1

Answers: 1

user13474103

Reputation:

How can I get exhaust list of functions available to grad_fn for backward() function in Pytorch?

pytorchautomatic-differentiation

Score: 0

Answers: 1

HenryS

Reputation: 21

Accurately finding the gradient of values from 2 vectors

juliainterpolationautomatic-differentiation

Score: 1

Answers: 1

loonatick

Reputation: 1157

What is the correct way of defining a differentiable function with scalar arguments that returns a vector/array?

swiftautomatic-differentiation

Score: 2

Answers: 0

MWB

Reputation: 12617

How can PyTorch-like automatic differentiation work in Rust, given that it does not allow multiple mutable references?

rustbackpropagationautomatic-differentiation

Score: 3

Answers: 2

JS4137

Reputation: 406

Why is the Jacobian of a 4D matrix calculated incorrectly by PyTorch's torch.autograd.functional.jacobian?

pytorchautomatic-differentiation

Score: 1

Answers: 1

0xbadf00d

Reputation: 18218

automatic differentiation and getting the next representable floating point value

c++c++20automatic-differentiation

Score: 1

Answers: 1

MOON

Reputation: 2811

Zygote cannot evaluate Hessian if the function argument is annotated

juliaautomatic-differentiation

Score: 0

Answers: 1

joel

Reputation: 7877

What is differentiable programming?

language-agnosticdifferentiationautomatic-differentiation

Score: 7

Answers: 3

BBB

Reputation: 75

How can I implement this function of torch.where and torch.sqrt in a better way so that autograd works?

pythonpytorchautogradautomatic-differentiation

Score: 0

Answers: 1

ZenDen

Reputation: 23

Is there a fast way of calculating 1000 Jacobians of a neural network?

python-3.xtensorflowneural-networkautomatic-differentiationgradienttape

Score: 0

Answers: 1

cardoza2

Reputation: 185

How to use parametric typing with structs that have many fields different types

juliaparametric-polymorphismautomatic-differentiation

Score: 1

Answers: 0

tmph

Reputation: 201

Running TensorFlow on a Numpy-only function

pythonnumpytensorflowautomatic-differentiation

Score: 0

Answers: 0

eliss

Reputation: 89

Difference in autograd.grad for same input

pythondeep-learningpytorchautogradautomatic-differentiation

Score: 1

Answers: 0

shmirrkk

Reputation: 61

How do I manually set partial derivatives for a multi-input function in pytorch?

pythonmachine-learningpytorchautogradautomatic-differentiation

Score: 2

Answers: 0

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StackOverflow Questions for Tag: automatic-differentiation

How to implement Carleman Matrix in Haskell?

solving an ODE using neural networks

JAX `custom_vjp` for functions with multiple outputs

JAX `vjp` fails for vmapped function with `custom_vjp`

JAX `vjp` does not recognize cotangent argument with `custom_vjp`

Failing to return gradients

How can I get exhaust list of functions available to grad_fn for backward() function in Pytorch?

Accurately finding the gradient of values from 2 vectors

What is the correct way of defining a differentiable function with scalar arguments that returns a vector/array?

How can PyTorch-like automatic differentiation work in Rust, given that it does not allow multiple mutable references?

Why is the Jacobian of a 4D matrix calculated incorrectly by PyTorch&#39;s torch.autograd.functional.jacobian?

automatic differentiation and getting the next representable floating point value

Zygote cannot evaluate Hessian if the function argument is annotated

What is differentiable programming?

How can I implement this function of torch.where and torch.sqrt in a better way so that autograd works?

Is there a fast way of calculating 1000 Jacobians of a neural network?

How to use parametric typing with structs that have many fields different types

Running TensorFlow on a Numpy-only function

Difference in autograd.grad for same input

How do I manually set partial derivatives for a multi-input function in pytorch?

Why is the Jacobian of a 4D matrix calculated incorrectly by PyTorch's torch.autograd.functional.jacobian?