Link the new tutorial in the readme

pnkraemer · Oct 11, 2023 · 4dace9b · 4dace9b
1 parent 45c5cef
commit 4dace9b
Show file tree

Hide file tree

Showing 2 changed files with 2 additions and 0 deletions.
diff --git a/README.md b/README.md
@@ -69,6 +69,7 @@ Determine the number of samples per batch as follows.
 - **Log-determinants:**  Use stochastic Lanczos quadrature to compute matrix functions. [(LINK)](https://pnkraemer.github.io/matfree/log_determinants/)
 - **Higher moments and UQ:** Compute means, variances, and other moments simultaneously. [(LINK)](https://pnkraemer.github.io/matfree/higher_moments/)
 - **Vector calculus:** Use matrix-free linear algebra to implement vector calculus. [(LINK)](https://pnkraemer.github.io/matfree/vector_calculus/)
+- **Pytree-valued states:** Combining neural-network Jacobians with stochastic Lanczos quadrature.
 
 
 

diff --git a/docs/index.md b/docs/index.md
@@ -69,6 +69,7 @@ Determine the number of samples per batch as follows.
 - **Log-determinants:**  Use stochastic Lanczos quadrature to compute matrix functions. [(LINK)](https://pnkraemer.github.io/matfree/log_determinants/)
 - **Higher moments and UQ:** Compute means, variances, and other moments simultaneously. [(LINK)](https://pnkraemer.github.io/matfree/higher_moments/)
 - **Vector calculus:** Use matrix-free linear algebra to implement vector calculus. [(LINK)](https://pnkraemer.github.io/matfree/vector_calculus/)
+- **Pytree-valued states:** Combining neural-network Jacobians with stochastic Lanczos quadrature.