Georgios Arvanitidis

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 27

Top Topics

Fisher Information

Maximum Likelihood Estimation

Riemannian Manifolds

Top Venues

Publications

Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo
Neural Contractive Dynamical Systems. CoRR (2024)
Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo
Neural Contractive Dynamical Systems. ICLR (2024)
Alison Pouplin, Hrittik Roy, Sidak Pal Singh, Georgios Arvanitidis
On the curvature of the loss landscape. CoRR (2023)
Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis
Riemannian Laplace approximations for Bayesian neural networks. NeurIPS (2023)
Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo
Reactive motion generation on learned Riemannian manifolds. Int. J. Robotics Res. 42 (10) (2023)
Ricardo Dominguez-Olmedo, Amir-Hossein Karimi, Georgios Arvanitidis, Bernhard Schölkopf
On Data Manifolds Entailed by Structural Causal Models. ICML (2023)
Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis
Riemannian Laplace approximations for Bayesian neural networks. CoRR (2023)
Hadi Beik Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo
Reactive Motion Generation on Learned Riemannian Manifolds. CoRR (2022)
Georgios Arvanitidis, Miguel González Duque, Alison Pouplin, Dimitrios Kalatzis, Søren Hauberg
Pulling back information geometry. AISTATS (2022)
Georgios Arvanitidis, Bogdan M. Georgiev, Bernhard Schölkopf
A prior-based approximate latent Riemannian metric. AISTATS (2022)
Hadi Beik Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo
Learning Riemannian Manifolds for Geodesic Motion Skills. Robotics: Science and Systems (2021)
Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf
Geometrically Enriched Latent Spaces. AISTATS (2021)
Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis
Bayesian Quadrature on Riemannian Data Manifolds. CoRR (2021)
Hadi Beik Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo
Learning Riemannian Manifolds for Geodesic Motion Skills. CoRR (2021)
Georgios Arvanitidis, Bogdan Georgiev, Bernhard Schölkopf
A prior-based approximate latent Riemannian metric. CoRR (2021)
Bogdan Georgiev, Lukas Franken, Mayukh Mukherjee, Georgios Arvanitidis
On the Impact of Stable Ranks in Deep Nets. CoRR (2021)
Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis
Bayesian Quadrature on Riemannian Data Manifolds. ICML (2021)
Georgios Arvanitidis, Miguel González Duque, Alison Pouplin, Dimitris Kalatzis, Søren Hauberg
Pulling back information geometry. CoRR (2021)
Dimitrios Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg
Variational Autoencoders with Riemannian Brownian Motion Priors. ICML (2020)
Dimitris Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg
Variational Autoencoders with Riemannian Brownian Motion Priors. CoRR (2020)
Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf
Geometrically Enriched Latent Spaces. CoRR (2020)
Georgios Arvanitidis, Søren Hauberg, Philipp Hennig, Michael Schober
Fast and Robust Shortest Paths on Manifolds Learned from Data. CoRR (2019)
Georgios Arvanitidis, Søren Hauberg, Philipp Hennig, Michael Schober
Fast and Robust Shortest Paths on Manifolds Learned from Data. AISTATS (2019)
Tao Yang, Georgios Arvanitidis, Dongmei Fu, Xiaogang Li, Søren Hauberg
Geodesic Clustering in Deep Generative Models. CoRR (2018)
Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg
Latent Space Oddity: on the Curvature of Deep Generative Models. ICLR (Poster) (2018)
Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg
Maximum Likelihood Estimation of Riemannian Metrics from Euclidean Data. GSI (2017)
Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg
A Locally Adaptive Normal Distribution. NIPS (2016)
Georgios Arvanitidis, Anastasios Tefas
Exploiting graph embedding in support vector machines. MLSP (2012)