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LEO: Learning Energy-based Models in Factor Graph Optimization

LEO: Learning Energy-based Models in Factor Graph Optimization

4 August 2021
Paloma Sodhi
Eric Dexheimer
Mustafa Mukadam
Stuart Anderson
Michael Kaess
ArXivPDFHTML

Papers citing "LEO: Learning Energy-based Models in Factor Graph Optimization"

13 / 13 papers shown
Title
Variational Potential Flow: A Novel Probabilistic Framework for
  Energy-Based Generative Modelling
Variational Potential Flow: A Novel Probabilistic Framework for Energy-Based Generative Modelling
Junn Yong Loo
Michelle Adeline
Arghya Pal
Vishnu Monn Baskaran
Chee-Ming Ting
Raphaël C.-W. Phan
DiffM
20
0
0
21 Jul 2024
Constrained Layout Generation with Factor Graphs
Constrained Layout Generation with Factor Graphs
Mohammed Haroon Dupty
Yanfei Dong
Sicong Leng
Guoji Fu
Yong Liang Goh
Wei Lu
Wee Sun Lee
3DV
28
4
0
30 Mar 2024
Revisiting Implicit Differentiation for Learning Problems in Optimal
  Control
Revisiting Implicit Differentiation for Learning Problems in Optimal Control
Ming Xu
Timothy Molloy
Stephen Gould
15
5
0
23 Oct 2023
Learning Covariances for Estimation with Constrained Bilevel
  Optimization
Learning Covariances for Estimation with Constrained Bilevel Optimization
Mohamad Qadri
Zachary Manchester
Michael Kaess
11
4
0
18 Sep 2023
Differentiable SLAM Helps Deep Learning-based LiDAR Perception Tasks
Differentiable SLAM Helps Deep Learning-based LiDAR Perception Tasks
Prashant Kumar
Dheeraj Vattikonda
Vedang Bhupesh Shenvi Nadkarni
Erqun Dong
Sabyasachi Sahoo
19
2
0
17 Sep 2023
Learning Observation Models with Incremental Non-Differentiable Graph
  Optimizers in the Loop for Robotics State Estimation
Learning Observation Models with Incremental Non-Differentiable Graph Optimizers in the Loop for Robotics State Estimation
Mohamad Qadri
Michael Kaess
16
4
0
05 Sep 2023
Placing by Touching: An empirical study on the importance of tactile
  sensing for precise object placing
Placing by Touching: An empirical study on the importance of tactile sensing for precise object placing
Luca Lach
Niklas Funk
R. Haschke
Séverin Lemaignan
Helge J. Ritter
Jan Peters
Georgia Chalvatzaki
19
10
0
05 Oct 2022
Theseus: A Library for Differentiable Nonlinear Optimization
Theseus: A Library for Differentiable Nonlinear Optimization
Luis Pineda
Taosha Fan
Maurizio Monge
S. Venkataraman
Paloma Sodhi
...
Austin S. Wang
Stuart Anderson
Jing Dong
Brandon Amos
Mustafa Mukadam
19
76
0
19 Jul 2022
Category-Independent Articulated Object Tracking with Factor Graphs
Category-Independent Articulated Object Tracking with Factor Graphs
Nick Heppert
Toki Migimatsu
Brent Yi
Claire Chen
Jeannette Bohg
13
22
0
07 May 2022
Probabilistic Tracking with Deep Factors
Probabilistic Tracking with Deep Factors
F. Jiang
Andrew Marmon
Ildebrando De Courten
M. Rasi
F. Dellaert
8
1
0
02 Dec 2021
How to Train Your Differentiable Filter
How to Train Your Differentiable Filter
Alina Kloss
Georg Martius
Jeannette Bohg
23
46
0
28 Dec 2020
How to Train Your Energy-Based Model for Regression
How to Train Your Energy-Based Model for Regression
Fredrik K. Gustafsson
Martin Danelljan
Radu Timofte
Thomas B. Schon
27
42
0
04 May 2020
ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D
  Cameras
ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras
Raul Mur-Artal
Juan D. Tardós
201
5,352
0
20 Oct 2016
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