Anton Mallasto

According to our database1, Anton Mallasto authored at least 14 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Learning representations that are closed-form Monge mapping optimal with application to domain adaptation.
Trans. Mach. Learn. Res., 2023

Understanding deep neural networks through the lens of their non-linearity.
CoRR, 2023

Beyond invariant representation learning: linearly alignable latent spaces for efficient closed-form domain adaptation.
CoRR, 2023

2021
Affine Transport for Sim-to-Real Domain Adaptation.
CoRR, 2021

Estimating 2-Sinkhorn Divergence between Gaussian Processes from Finite-Dimensional Marginals.
CoRR, 2021

Bayesian Inference for Optimal Transport with Stochastic Cost.
Proceedings of the Asian Conference on Machine Learning, 2021

2020
Entropy-Regularized 2-Wasserstein Distance between Gaussian Measures.
CoRR, 2020

2019
How Well Do WGANs Estimate the Wasserstein Metric?
CoRR, 2019

(q, p)-Wasserstein GANs: Comparing Ground Metrics for Wasserstein GANs.
CoRR, 2019

A Formalization of the Natural Gradient Method for General Similarity Measures.
Proceedings of the Geometric Science of Information - 4th International Conference, 2019

Simulation of Conditioned Diffusions on the Flat Torus.
Proceedings of the Geometric Science of Information - 4th International Conference, 2019

Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Wrapped Gaussian Process Regression on Riemannian Manifolds.
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.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017


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