Publications
"Neural Contractive Dynamical Systems"
Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo
International Conference on Representation Learning (ICLR), 2024
pdf
"On the curvature of the loss landscape"
Alison Pouplin, Hrittik Roy, Sidak Pal Singh, Georgios Arvanitidis
arXiv preprit, 2023
pdf
"Riemannian Laplace approximations for Bayesian neural networks"
Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis
Neural Information Processing Systems (NeurIPS), 2023
pdf
"On Data Manifolds Entailed by Structural Causal Models"
Ricardo Dominguez-Olmedo, Amir-Hossein Karimi, Georgios Arvanitidis, Bernhard Schölkopf
International Conference on Machine Learning (ICML), 2023
pdf
"Reactive Motion Generation on Learned Riemannian Manifolds"
Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo
International Journal of Robotics Research (IJRR), 2023
pdf publisher's site video
"A prior-based approximate latent Riemannian metric"
Georgios Arvanitidis, Bogdan Georgiev, Bernhard Schölkopf
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
pdf
"Pulling back information geometry"
Georgios Arvanitidis, Miguel González-Duque, Alison Pouplin, Dimitris Kalatzis, Søren Hauberg
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
pdf
"Learning Riemannian Manifolds for Geodesic Motion Skills"
Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo
Robotics: Science and Systems (R:SS), 2021
pdf
"Bayesian Quadrature on Riemannian Data Manifolds"
Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis
International Conference on Machine Learning (ICML), 2021
pdf video
"Geometrically Enriched Latent Spaces"
Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
pdf
"On the Impact of Stable Ranks in Deep Nets"
Bogdan Georgiev, Lukas Franken, Mayukh Mukherjee, Georgios Arvanitidis
arxiv preprint, 2021
pdf
"Variational Autoencoders with Riemannian Brownian Motion Priors"
Dimitris Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg
International Conference on Machine Learning (ICML), 2020
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"Fast and Robust Shortest Paths on Manifolds Learned from Data"
Georgios Arvanitidis, Søren Hauberg, Philipp Hennig, Michael Schober
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
pdf
"Latent Space Oddity: on the Curvature of Deep Generative Models"
Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg
International Conference on Learning Representations (ICLR), 2018
pdf arXiv
"Geodesic Clustering in Deep Generative Models"
Tao Yang, Georgios Arvanitidis, Dongmei Fu, Xiaogang Li, Søren Hauberg
arXiv preprint, 2018
pdf
"Maximum likelihood estimation of Riemannian metrics from Euclidean data"
Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg
Geometric Science of Information (GSI), 2017
pdf
"A Locally Adaptive Normal Distribution"
Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg
Neural Information Processing Systems (NeurIPS), 2016
pdf errata
"Exploiting Graph Embedding in Support Vector Machines"
Georgios Arvanitidis, Anastasios Tefas
IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2012
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