Mallasto, Anton

6 publications

CVPR 2025 From AlexNet to Transformers: Measuring the Non-Linearity of Deep Neural Networks with Affine Optimal Transport Quentin Bouniot, Ievgen Redko, Anton Mallasto, Charlotte Laclau, Oliver Struckmeier, Karol Arndt, Markus Heinonen, Ville Kyrki, Samuel Kaski

ICMLW 2024 From AlexNet to Transformers: Measuring the Non-Linearity of Deep Neural Networks with Affine Optimal Transport Quentin Bouniot, Ievgen Redko, Anton Mallasto, Charlotte Laclau, Oliver Struckmeier, Karol Arndt, Markus Heinonen, Ville Kyrki, Samuel Kaski

TMLR 2023 Learning Representations That Are Closed-Form Monge Mapping Optimal with Application to Domain Adaptation Oliver Struckmeier, Ievgen Redko, Anton Mallasto, Karol Arndt, Markus Heinonen, Ville Kyrki

ACML 2021 Bayesian Inference for Optimal Transport with Stochastic Cost Anton Mallasto, Markus Heinonen, Samuel Kaski

AISTATS 2019 Probabilistic Riemannian Submanifold Learning with Wrapped Gaussian Process Latent Variable Models Anton Mallasto, Søren Hauberg, Aasa Feragen

NeurIPS 2017 Learning from Uncertain Curves: The 2-Wasserstein Metric for Gaussian Processes Anton Mallasto, Aasa Feragen