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ORCIDGeorgios Arvanitidis
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2020 – today
- 2024
[c14]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo:
Neural Contractive Dynamical Systems. ICLR 2024- [i13]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo:
Neural Contractive Dynamical Systems. CoRR abs/2401.09352 (2024) - 2023
- [j1]Hadi Beik-Mohammadi
, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo:
Reactive motion generation on learned Riemannian manifolds. Int. J. Robotics Res. 42(10): 729-754 (2023) - [c13]Ricardo Dominguez-Olmedo, Amir-Hossein Karimi, Georgios Arvanitidis, Bernhard Schölkopf:
On Data Manifolds Entailed by Structural Causal Models. ICML 2023: 8188-8201 - [c12]Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis:
Riemannian Laplace approximations for Bayesian neural networks. NeurIPS 2023 - [i12]Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis:
Riemannian Laplace approximations for Bayesian neural networks. CoRR abs/2306.07158 (2023) - [i11]Alison Pouplin, Hrittik Roy, Sidak Pal Singh, Georgios Arvanitidis:
On the curvature of the loss landscape. CoRR abs/2307.04719 (2023) - 2022
- [c11]Georgios Arvanitidis, Bogdan M. Georgiev, Bernhard Schölkopf:
A prior-based approximate latent Riemannian metric. AISTATS 2022: 4634-4658 - [c10]Georgios Arvanitidis, Miguel González Duque, Alison Pouplin, Dimitrios Kalatzis, Søren Hauberg:
Pulling back information geometry. AISTATS 2022: 4872-4894 - [i10]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo:
Reactive Motion Generation on Learned Riemannian Manifolds. CoRR abs/2203.07761 (2022) - 2021
- [c9]Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf:
Geometrically Enriched Latent Spaces. AISTATS 2021: 631-639 - [c8]Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis:
Bayesian Quadrature on Riemannian Data Manifolds. ICML 2021: 3459-3468 - [c7]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo:
Learning Riemannian Manifolds for Geodesic Motion Skills. Robotics: Science and Systems 2021 - [i9]Christian Fröhlich, Alexandra Gessner, Philipp Hennig, Bernhard Schölkopf, Georgios Arvanitidis:
Bayesian Quadrature on Riemannian Data Manifolds. CoRR abs/2102.06645 (2021) - [i8]Georgios Arvanitidis, Bogdan Georgiev, Bernhard Schölkopf:
A prior-based approximate latent Riemannian metric. CoRR abs/2103.05290 (2021) - [i7]Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo:
Learning Riemannian Manifolds for Geodesic Motion Skills. CoRR abs/2106.04315 (2021) - [i6]Georgios Arvanitidis, Miguel González Duque, Alison Pouplin, Dimitris Kalatzis, Søren Hauberg:
Pulling back information geometry. CoRR abs/2106.05367 (2021) - [i5]Bogdan Georgiev, Lukas Franken, Mayukh Mukherjee, Georgios Arvanitidis:
On the Impact of Stable Ranks in Deep Nets. CoRR abs/2110.02333 (2021) - 2020
- [c6]Dimitrios Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg:
Variational Autoencoders with Riemannian Brownian Motion Priors. ICML 2020: 5053-5066 - [i4]Dimitris Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg:
Variational Autoencoders with Riemannian Brownian Motion Priors. CoRR abs/2002.05227 (2020) - [i3]Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf:
Geometrically Enriched Latent Spaces. CoRR abs/2008.00565 (2020)
2010 – 2019
- 2019
- [c5]Georgios Arvanitidis, Søren Hauberg, Philipp Hennig, Michael Schober:
Fast and Robust Shortest Paths on Manifolds Learned from Data. AISTATS 2019: 1506-1515 - [i2]Georgios Arvanitidis, Søren Hauberg, Philipp Hennig, Michael Schober:
Fast and Robust Shortest Paths on Manifolds Learned from Data. CoRR abs/1901.07229 (2019) - 2018
- [c4]Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg:
Latent Space Oddity: on the Curvature of Deep Generative Models. ICLR (Poster) 2018 - [i1]Tao Yang, Georgios Arvanitidis, Dongmei Fu, Xiaogang Li, Søren Hauberg:
Geodesic Clustering in Deep Generative Models. CoRR abs/1809.04747 (2018) - 2017
- [c3]Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg:
Maximum Likelihood Estimation of Riemannian Metrics from Euclidean Data. GSI 2017: 38-46 - 2016
- [c2]Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg:
A Locally Adaptive Normal Distribution. NIPS 2016: 4251-4259 - 2012
- [c1]Georgios Arvanitidis, Anastasios Tefas:
Exploiting graph embedding in support vector machines. MLSP 2012: 1-6
Coauthor Index
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last updated on 2024-07-30 21:37 CEST by the dblp team
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