2 papers
stat.ME2026
Beyond Laplace: Closed-form wrapped Gaussian posterior approximations on statistical manifolds
Marcelo Hartmann, Luu Hoang Phuc Hau, Anton Mallasto +8
In Bayesian statistics, the Laplace approximation provides a computationally efficient approximation to posterior distributions. However, its Gaussian form restricts it to elliptic…
cs.LG2025
From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport
Quentin Bouniot, Ievgen Redko, Anton Mallasto +6
In the last decade, we have witnessed the introduction of several novel deep neural network (DNN) architectures exhibiting ever-increasing performance across diverse tasks. Explain…