Georgios Arvanitidis

Orcid: 0000-0002-0377-2976

According to our database1, Georgios Arvanitidis authored at least 19 papers between 2012 and 2024.

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

Timeline

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Links

On csauthors.net:

Bibliography

2024
Neural Contractive Dynamical Systems.
CoRR, 2024

2023
Reactive motion generation on learned Riemannian manifolds.
Int. J. Robotics Res., September, 2023

On the curvature of the loss landscape.
CoRR, 2023

Riemannian Laplace approximations for Bayesian neural networks.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On Data Manifolds Entailed by Structural Causal Models.
Proceedings of the International Conference on Machine Learning, 2023

2022
A prior-based approximate latent Riemannian metric.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Pulling back information geometry.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
On the Impact of Stable Ranks in Deep Nets.
CoRR, 2021

A prior-based approximate latent Riemannian metric.
CoRR, 2021

Learning Riemannian Manifolds for Geodesic Motion Skills.
Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

Bayesian Quadrature on Riemannian Data Manifolds.
Proceedings of the 38th International Conference on Machine Learning, 2021

Geometrically Enriched Latent Spaces.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Variational Autoencoders with Riemannian Brownian Motion Priors.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Fast and Robust Shortest Paths on Manifolds Learned from Data.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Geodesic Clustering in Deep Generative Models.
CoRR, 2018

Latent Space Oddity: on the Curvature of Deep Generative Models.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Maximum Likelihood Estimation of Riemannian Metrics from Euclidean Data.
Proceedings of the Geometric Science of Information - Third International Conference, 2017

2016
A Locally Adaptive Normal Distribution.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2012
Exploiting graph embedding in support vector machines.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012


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