Anton Mallasto

According to our database, Anton Mallasto authored at least 14 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

Trans. Mach. Learn. Res., 2023

Understanding deep neural networks through the lens of their non-linearity.

Quentin Bouniot, Ievgen Redko, Anton Mallasto, Charlotte Laclau, Karol Arndt, Oliver Struckmeier, Markus Heinonen, Ville Kyrki, Samuel Kaski

CoRR, 2023

Beyond invariant representation learning: linearly alignable latent spaces for efficient closed-form domain adaptation.

Oliver Struckmeier, Ievgen Redko, Anton Mallasto, Karol Arndt, Markus Heinonen, Ville Kyrki

CoRR, 2023

2021

Affine Transport for Sim-to-Real Domain Adaptation.

Anton Mallasto, Karol Arndt, Markus Heinonen, Samuel Kaski, Ville Kyrki

CoRR, 2021

Estimating 2-Sinkhorn Divergence between Gaussian Processes from Finite-Dimensional Marginals.

Anton Mallasto

CoRR, 2021

Bayesian Inference for Optimal Transport with Stochastic Cost.

Anton Mallasto, Markus Heinonen, Samuel Kaski

Proceedings of the Asian Conference on Machine Learning, 2021

2020

Entropy-Regularized 2-Wasserstein Distance between Gaussian Measures.

Anton Mallasto, Augusto Gerolin, Hà Quang Minh

CoRR, 2020

2019

How Well Do WGANs Estimate the Wasserstein Metric?

Anton Mallasto, Guido Montúfar, Augusto Gerolin

CoRR, 2019

(q, p)-Wasserstein GANs: Comparing Ground Metrics for Wasserstein GANs.

Anton Mallasto, Jes Frellsen, Wouter Boomsma, Aasa Feragen

CoRR, 2019

A Formalization of the Natural Gradient Method for General Similarity Measures.

Anton Mallasto, Tom C. J. Dela Haije, Aasa Feragen

Proceedings of the Geometric Science of Information - 4th International Conference, 2019

Simulation of Conditioned Diffusions on the Flat Torus.

Mathias Højgaard Jensen, Anton Mallasto, Stefan Sommer

Proceedings of the Geometric Science of Information - 4th International Conference, 2019

Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models.

Anton Mallasto, Søren Hauberg, Aasa Feragen

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Wrapped Gaussian Process Regression on Riemannian Manifolds.

Anton Mallasto, Aasa Feragen

Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

2017

Learning from uncertain curves: The 2-Wasserstein metric for Gaussian processes.

Anton Mallasto, Aasa Feragen

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017