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I played with Enzyme a little bit, and I suspect it's not ready for use with our package. It can't differentiate simple ODEs at present. There's a fair amount of linear algebra in OrdinaryDiffEq, so i…
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Hi,
I am trying to integrate a vector field with jumps in the derivative and experience a high integration error when the derivative jumps. As a solution attempt, I would like to split the integrat…
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I define the function f(x) = x*(1-x^(1.1)). It is twice differentiable at x=0. Above that, not. At live.sympy.org I did:
```
>>> gamma = 1.1
>>> for n in range(10): print(n, diff(x*(1-pow(x, gamm…
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- [x] Data does not support matrix shape
- [x] ParamView does not support matrix shape
- [x] Param does not support matrix shape
- [x] Constant does not support vector or matrix shape
- [x] Dot on…
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TF provides the `TensorArray` to make automatic iteration and stacking efficient in `scan` or `while_loop`.
The naive variant with gathering and concatenating or dynamic updates would be inefficien…
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**Question❓**
Is it expected that the gradient for ReverseDiff and FiniteDiff disagree, even though the solver steps to almost exactly the same times? The difference goes away when the tolerances a…
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This was brought up by Aki
The page is https://en.wikipedia.org/wiki/Stan_(software)
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Hi, developers!
My question is, is there any plan to support Convex.jl here with AD like [cvxpylayers](https://github.com/cvxgrp/cvxpylayers)?
For AD of the solution to (convex) optimization probl…
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```julia
julia> derivative(x->x*derivative(y->x+y,1),1)
ERROR: MethodError: no method matching exprtype(::Core.Compiler.IRCode, ::String)
Closest candidates are:
exprtype(::Core.Compiler.IRCode,…
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I am using a trick to compute the Fisher information matrix from a log likelihood with JAX by taking the Hessian with partially disabled second order derivatives. In particular I apply `stop_gradient`…