Anton Mallasto

Publication Activity (10 Years)

Years Active: 2017-2023
Publications (10 Years): 17

Top Topics

Gaussian Process

Top Venues

Publications

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