Bayesian Optimization Meets Riemannian Manifolds in Robot Learning

11 October 2019

Papers citing "Bayesian Optimization Meets Riemannian Manifolds in Robot Learning"

32 / 32 papers shown

Title
TamedPUMA: safe and stable imitation learning with geometric fabrics Saray Bakker Rodrigo Pérez-Dattari Cosimo Della Santina Wendelin Böhmer Javier Alonso-Mora 58 0 0 21 Mar 2025
High-Dimensional Bayesian Optimization via Random Projection of Manifold Subspaces Quoc-Anh Hoang Nguyen The Hung Tran 93 1 0 21 Dec 2024
Bayesian Optimal Experimental Design for Robot Kinematic Calibration Ersin Daş Thomas Touma J. W. Burdick 32 0 0 17 Sep 2024
A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences Miguel González Duque Richard Michael Simon Bartels Yevgen Zainchkovskyy Søren Hauberg Wouter Boomsma 46 4 0 07 Jun 2024
Riemannian Bilevel Optimization Sanchayan Dutta Xiang Cheng S. Sra 44 0 0 22 May 2024
Convergence and Complexity Guarantee for Inexact First-order Riemannian Optimization Algorithms Yuchen Li Laura Balzano Deanna Needell Hanbaek Lyu 25 1 0 05 May 2024
Learning Reduced-Order Soft Robot Controller Chen Liang Xifeng Gao Kui Wu Zherong Pan 13 2 0 03 Nov 2023
A Bayesian optimization framework for the automatic tuning of MPC-based shared controllers A. V. D. Horst Bas Meere Dinesh Krishnamoorthy Saray Bakker Bram van de Vrande Henry Stoutjesdijk Marco Alonso Elena Torta 32 1 0 02 Nov 2023
Unraveling the Single Tangent Space Fallacy: An Analysis and Clarification for Applying Riemannian Geometry in Robot Learning Noémie Jaquier Leonel Rozo Tamim Asfour 36 7 0 11 Oct 2023
Wasserstein Gradient Flows for Optimizing Gaussian Mixture Policies Hanna Ziesche Leonel Rozo 26 5 0 17 May 2023
The e-Bike Motor Assembly: Towards Advanced Robotic Manipulation for Flexible Manufacturing Leonel Rozo A. Kupcsik Philipp Schillinger Meng Guo R. Krug ... Patrick Kesper Sabrina Hoppe Hanna Ziesche M. Burger Kai O. Arras 38 5 0 20 Apr 2023
The Gaussian kernel on the circle and spaces that admit isometric embeddings of the circle Nathael Da Costa Cyrus Mostajeran Juan-Pablo Ortega BDL 17 4 0 21 Feb 2023
Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces I. Azangulov A. Smolensky Alexander Terenin Viacheslav Borovitskiy 32 14 0 30 Jan 2023
Gaussian Process regression over discrete probability measures: on the non-stationarity relation between Euclidean and Wasserstein Squared Exponential Kernels Antonio Candelieri Andrea Ponti Francesco Archetti 14 1 0 02 Dec 2022
Optimization on Manifolds via Graph Gaussian Processes Hwanwoo Kim D. Sanz-Alonso Ruiyi Yang 40 2 0 20 Oct 2022
Geometric Reinforcement Learning For Robotic Manipulation Naseem Alhousani Matteo Saveriano Ibrahim Sevinc Talha Abdulkuddus Hatice Kose Fares J. Abu-Dakka 41 6 0 14 Oct 2022
Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact case I. Azangulov A. Smolensky Alexander Terenin Viacheslav Borovitskiy 39 21 0 31 Aug 2022
Recent Advances in Bayesian Optimization Xilu Wang Yaochu Jin Sebastian Schmitt Markus Olhofer 40 200 0 07 Jun 2022
ODBO: Bayesian Optimization with Search Space Prescreening for Directed Protein Evolution Lixue Cheng Ziyi Yang Chang-Yu Hsieh Ben Liao Shengyu Zhang 30 6 0 19 May 2022
Reactive Motion Generation on Learned Riemannian Manifolds Hadi Beik-Mohammadi Søren Hauberg Georgios Arvanitidis Gerhard Neumann Leonel Rozo 30 11 0 15 Mar 2022
Geometry-aware Bayesian Optimization in Robotics using Riemannian Matérn Kernels Noémie Jaquier Viacheslav Borovitskiy A. Smolensky Alexander Terenin Tamim Asfour Leonel Rozo 34 35 0 02 Nov 2021
Orientation Probabilistic Movement Primitives on Riemannian Manifolds Leonel Rozo Vedant Dave 13 35 0 28 Oct 2021
Adversarial Attacks on Gaussian Process Bandits E. Han Jonathan Scarlett GP AAML 11 6 0 16 Oct 2021
Learning Riemannian Manifolds for Geodesic Motion Skills Hadi Beik-Mohammadi Søren Hauberg Georgios Arvanitidis Gerhard Neumann Leonel Rozo 32 33 0 08 Jun 2021
Efficient Hyperparameter Optimization for Physics-based Character Animation Zeshi Yang Zhiqi Yin AI4CE 32 9 0 26 Apr 2021
Good practices for Bayesian Optimization of high dimensional structured spaces E. Siivola Javier I. González Andrei Paleyes Aki Vehtari 30 37 0 31 Dec 2020
High-Dimensional Bayesian Optimization via Tree-Structured Additive Models E. Han Ishank Arora Jonathan Scarlett TPM AI4CE 33 17 0 24 Dec 2020
Cautious Bayesian Optimization for Efficient and Scalable Policy Search Lukas P. Frohlich Melanie Zeilinger Edgar D. Klenske OffRL 39 13 0 18 Nov 2020
High-Dimensional Bayesian Optimization via Nested Riemannian Manifolds Noémie Jaquier Leonel Rozo 22 24 0 21 Oct 2020
Learning and Sequencing of Object-Centric Manipulation Skills for Industrial Tasks Leonel Rozo Meng Guo A. Kupcsik M. Todescato Philipp Schillinger ... M. Ochs Markus Spies Nicolai Waniek Patrick Kesper Mathias Buerger 14 18 0 24 Aug 2020
Analysis and Transfer of Human Movement Manipulability in Industry-like Activities Noémie Jaquier Leonel Rozo Sylvain Calinon 6 14 0 04 Aug 2020
Matérn Gaussian processes on Riemannian manifolds Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 22 120 0 17 Jun 2020