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In Laplace approximation, the Hessian of the loss function is computed for quadratic approximation. Can this package be used to do a block-diagonal approximation of the Hessian at the minimum? If yes, could you please show (using jax and flax) how to approximate it and define a quadratic approximation of the loss function (which should be something like 1/2 (theta - theta_star)^T H(L)(theta_star) (theta - theta_star), where theta_star is the minimum and H(L) is the Hessian of the loss function)?
The text was updated successfully, but these errors were encountered:
In Laplace approximation, the Hessian of the loss function is computed for quadratic approximation. Can this package be used to do a block-diagonal approximation of the Hessian at the minimum? If yes, could you please show (using
jax
andflax
) how to approximate it and define a quadratic approximation of the loss function (which should be something like1/2 (theta - theta_star)^T H(L)(theta_star) (theta - theta_star)
, wheretheta_star
is the minimum andH(L)
is the Hessian of the loss function)?The text was updated successfully, but these errors were encountered: