Anton Mallasto

18 papers A* 2A 1C 1Journal 11Unranked 3
YearRankTypeTitle / Venue / Authors
2025 A* conf
From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport.
CVPR
Quentin Bouniot, Ievgen Redko, Anton Mallasto, Charlotte Laclau, Oliver Struckmeier, Karol Arndt, Markus Heinonen, Ville Kyrki, Samuel Kaski
2023 J jnl
Beyond invariant representation learning: linearly alignable latent spaces for efficient closed-form domain adaptation.
CoRR
Oliver Struckmeier, Ievgen Redko, Anton Mallasto, Karol Arndt, Markus Heinonen, Ville Kyrki
2023 J jnl
Learning representations that are closed-form Monge mapping optimal with application to domain adaptation.
Trans. Mach. Learn. Res.
Oliver Struckmeier, Ievgen Redko, Anton Mallasto, Karol Arndt, Markus Heinonen, Ville Kyrki
2023 J jnl
Understanding deep neural networks through the lens of their non-linearity.
CoRR
Quentin Bouniot, Ievgen Redko, Anton Mallasto, Charlotte Laclau, Karol Arndt, Oliver Struckmeier, Markus Heinonen, Ville Kyrki, Samuel Kaski
2021 J jnl
Affine Transport for Sim-to-Real Domain Adaptation.
CoRR
Anton Mallasto, Karol Arndt, Markus Heinonen, Samuel Kaski, Ville Kyrki
2021 C conf
Bayesian Inference for Optimal Transport with Stochastic Cost.
ACML
Anton Mallasto, Markus Heinonen, Samuel Kaski
2021 J jnl
Estimating 2-Sinkhorn Divergence between Gaussian Processes from Finite-Dimensional Marginals.
CoRR
Anton Mallasto
2020 J jnl
Bayesian Inference for Optimal Transport with Stochastic Cost.
CoRR
Anton Mallasto, Markus Heinonen, Samuel Kaski
2020 J jnl
Entropy-Regularized 2-Wasserstein Distance between Gaussian Measures.
CoRR
Anton Mallasto, Augusto Gerolin, Hà Quang Minh
2019 J jnl
(q, p)-Wasserstein GANs: Comparing Ground Metrics for Wasserstein GANs.
CoRR
Anton Mallasto, Jes Frellsen, Wouter Boomsma, Aasa Feragen
2019 J jnl
A Formalization of The Natural Gradient Method for General Similarity Measures.
CoRR
Anton Mallasto, Tom C. J. Dela Haije, Aasa Feragen
2019 — conf
A Formalization of the Natural Gradient Method for General Similarity Measures.
GSI
Anton Mallasto, Tom C. J. Dela Haije, Aasa Feragen
2019 J jnl
How Well Do WGANs Estimate the Wasserstein Metric?
CoRR
Anton Mallasto, Guido Montúfar, Augusto Gerolin
2019 A conf
Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models.
AISTATS
Anton Mallasto, Søren Hauberg, Aasa Feragen
2019 — conf
Simulation of Conditioned Diffusions on the Flat Torus.
GSI
Mathias Højgaard Jensen, Anton Mallasto, Stefan Sommer
2018 J jnl
Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models.
CoRR
Anton Mallasto, Søren Hauberg, Aasa Feragen
2018 A* conf
Wrapped Gaussian Process Regression on Riemannian Manifolds.
CVPR
Anton Mallasto, Aasa Feragen
2017 — conf
Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes.
NIPS
Anton Mallasto, Aasa Feragen