-
In the notebooks on the documentation here:
https://jax.readthedocs.io/en/latest/notebooks/autodiff_cookbook.html
The author describes topics that he would like to showcase in a future Autodiff co…
-
CUTEst 2.2 added routines for the (Fritz) John function, defined as
$$
\mathcal{J}(x,\lambda_0,\lambda) = \lambda_0 f(x) + \langle \lambda, c(x) \rangle
$$
(for more details please see https:/…
-
I need to design a (Fisher) kernel that is of the format:
k(x1, x2) = ∇θx1T **H** ∇θx2,
Where **H** = ∇θ[∇θ(KL)], is the hessian of KL divergence.
…
-
These two methods both compute the multiplication of a (approximate) Hessian and a vector. This is commonly refered to as a `Hessian_vector_product`. Renaming the current methods was first discussed h…
-
There are a bunch of autodiff functors that are implemented in Stan but not exposed yet in BridgeStan. The two most basic are already done. Most of them other than directional derivatives require f…
-
```
/gpfs/home6/scur0399/development/dl2/.venv/lib/python3.11/site-packages/torch/autograd/graph.py:744: UserWarning: Using backward() with create_graph=True will create a reference cycle between the…
dgcnz updated
3 months ago
-
Trying to use the minimize function with methods
- trust-ncg
- dogleg
- newton-exact
- trust-exact
- trust-krylov
But succeeds with the other methods. Presumably, the other methods aren…
-
Minimal test case:
```python
import tangent
import numpy as np
def forward(theta, states):
return states
def loss(theta, states, actions):
err = forward(theta, actions)
retur…
-
In hessian.py
When I tried to run the following code,
Hv = hessian_vector_product(gradsH, params, v)
The error comes out.
Is there any idea how to resolve this issue?
-
I'd like to apply Newton's method on a convex problem. When I try `jaxopt.ScipyMinimize` with `method="trust-exact"` I get the error:
```
ValueError: Hessian matrix is required for trust region ex…