StackOverflow Questions for Tag: automatic-differentiation

Amin Rezaei

Reputation: 376

Computing Gradients of Weighted State Averages in PyTorch Models

deep-learningpytorchautogradautomatic-differentiationautodiff

Score: 2

Answers: 0

Evan Pu

Reputation: 2187

how to apply gradients manually in pytorch

pytorchmathematical-optimizationautogradautomatic-differentiation

Score: 13

Answers: 1

JS4137

Reputation: 406

What is wrong with this implementation of matmul for automatic differentiation?

rustautomatic-differentiation

Score: 0

Answers: 1

Ian Holmes

Reputation: 95

How can I implement a vmappable sum over a dynamic range in Jax?

pythonnumpyjaxautomatic-differentiationautodiff

Score: 2

Answers: 1

roLEB

Reputation: 1

can't make my ForwardDiff.gradient function work

juliaeconomicsautomatic-differentiation

Score: 0

Answers: 0

MolochHorridus

Reputation: 57

Tensorflow loses track of variables/gradients after multiplication with constant tensor

pythontensorflowtensorflow2.0automatic-differentiation

Score: 2

Answers: 1

Jim Raynor

Reputation: 143

Confused about evaluating vector-Jacobian-product with non-identity vectors (JAX)

juliaderivativejaxautomatic-differentiationautodiff

Score: 1

Answers: 1

Dan Leonte

Reputation: 73

computational complexity of higher order derivatives with AD in jax

tensorflowtorchjaxtaylor-seriesautomatic-differentiation

Score: 1

Answers: 2

Jim Raynor

Reputation: 143

How to use and interpret JAX Vector-Jacobian Product (VJP) for this example?

odedifferential-equationsjaxautomatic-differentiationautodiff

Score: 1

Answers: 1

Thomas Wagenaar

Reputation: 6779

How to get the gradients of network parameters for a derivative-based loss?

pythonpytorchgradientbackpropagationautomatic-differentiation

Score: 0

Answers: 1

Marco Tulio Angulo

Reputation: 11

Using JuMP inside a Turing model

juliabayesianjulia-jumpautomatic-differentiationprobabilistic-programming

Score: 1

Answers: 1

Lars Gebraad

Reputation: 163

How to use tf.gradients within a model and still use a custom training loop?

pythontensorflowmachine-learningkerasautomatic-differentiation

Score: 0

Answers: 1

David H. J.

Reputation: 412

Can tf.gradienttape() calculate gradient of other library's function

pythontensorflowkerasautomatic-differentiationgradienttape

Score: 1

Answers: 1

Dan Leonte

Reputation: 73

jax minimization with stochastically estimated gradients

randommathematical-optimizationscipy-optimizejaxautomatic-differentiation

Score: 0

Answers: 1

juanmvenegas

Reputation: 117

Trouble writing OptimizationFunction for automatic forward differentiation during Parameter Estimation of an ODEProblem

optimizationjuliaautomatic-differentiation

Score: 2

Answers: 2

Dan Leonte

Reputation: 73

jax automatic differentiation

pythontensorflowjaxautomatic-differentiation

Score: 1

Answers: 1

tsbertalan

Reputation: 1550

What is the correct way to use a PyTorch Module inside a PyTorch Function?

pythonneural-networkpytorchautomatic-differentiation

Score: 1

Answers: 2

Silas

Reputation: 13

Derivative of Scalar Expansion in PyTorch

pythonpytorchderivativeautomatic-differentiation

Score: 0

Answers: 2

Sumanta Roy

Reputation: 21

How to take a derivative of one of the outputs of a neural network (involving batched inputs) with respect to inputs?

machine-learningneural-networkjaxautomatic-differentiation

Score: 1

Answers: 1

Deecer

Reputation: 51

Why does jax.grad(lambda v: jnp.linalg.norm(v-v))(jnp.ones(2)) produce nans?

pythonjaxautomatic-differentiation

Score: 1

Answers: 1

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StackOverflow Questions for Tag: automatic-differentiation

Computing Gradients of Weighted State Averages in PyTorch Models

how to apply gradients manually in pytorch

What is wrong with this implementation of matmul for automatic differentiation?

How can I implement a vmappable sum over a dynamic range in Jax?

can&#39;t make my ForwardDiff.gradient function work

Tensorflow loses track of variables/gradients after multiplication with constant tensor

Confused about evaluating vector-Jacobian-product with non-identity vectors (JAX)

computational complexity of higher order derivatives with AD in jax

How to use and interpret JAX Vector-Jacobian Product (VJP) for this example?

How to get the gradients of network parameters for a derivative-based loss?

Using JuMP inside a Turing model

How to use tf.gradients within a model and still use a custom training loop?

Can tf.gradienttape() calculate gradient of other library&#39;s function

jax minimization with stochastically estimated gradients

Trouble writing OptimizationFunction for automatic forward differentiation during Parameter Estimation of an ODEProblem

jax automatic differentiation

What is the correct way to use a PyTorch Module inside a PyTorch Function?

Derivative of Scalar Expansion in PyTorch

How to take a derivative of one of the outputs of a neural network (involving batched inputs) with respect to inputs?

Why does jax.grad(lambda v: jnp.linalg.norm(v-v))(jnp.ones(2)) produce nans?

can't make my ForwardDiff.gradient function work

Can tf.gradienttape() calculate gradient of other library's function