Rico Jonschkowski

Orcid: 0000-0001-6422-0262

According to our database1, Rico Jonschkowski authored at least 26 papers between 2014 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2022
Conditional Object-Centric Learning from Video.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
A Metric Space Perspective on Self-Supervised Policy Adaptation.
IEEE Robotics Autom. Lett., 2021

MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale.
CoRR, 2021

The Distracting Control Suite - A Challenging Benchmark for Reinforcement Learning from Pixels.
CoRR, 2021

Correction to: Four aspects of building robotic systems: lessons from the Amazon Picking Challenge 2015.
Auton. Robots, 2021

SMURF: Self-Teaching Multi-Frame Unsupervised RAFT With Full-Image Warping.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Adaptive Intermediate Representations for Video Understanding.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

Scaling Up Multi-Task Robotic Reinforcement Learning.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020
Learning Object-Centric Video Models by Contrasting Sets.
CoRR, 2020

A Geometric Perspective on Self-Supervised Policy Adaptation.
CoRR, 2020

Towards Differentiable Resampling.
CoRR, 2020

Differentiable Mapping Networks: Learning Structured Map Representations for Sparse Visual Localization.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

What Matters in Unsupervised Optical Flow.
Proceedings of the Computer Vision - ECCV 2020, 2020

KeyPose: Multi-View 3D Labeling and Keypoint Estimation for Transparent Objects.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Towards Object Detection from Motion.
CoRR, 2019

State Representation Learning with Robotic Priors for Partially Observable Environments.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Depth From Videos in the Wild: Unsupervised Monocular Depth Learning From Unknown Cameras.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018
Learning robotic perception through prior knowledge.
PhD thesis, 2018

Four aspects of building robotic systems: lessons from the Amazon Picking Challenge 2015.
Auton. Robots, 2018

Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors.
Proceedings of the Robotics: Science and Systems XIV, 2018

2017
PVEs: Position-Velocity Encoders for Unsupervised Learning of Structured State Representations.
CoRR, 2017

2016
Lessons from the Amazon Picking Challenge: Four Aspects of Building Robotic Systems.
Proceedings of the Robotics: Science and Systems XII, University of Michigan, Ann Arbor, Michigan, USA, June 18, 2016

Probabilistic multi-class segmentation for the Amazon Picking Challenge.
Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

2015
Contextual Learning.
CoRR, 2015

Learning state representations with robotic priors.
Auton. Robots, 2015

2014
State Representation Learning in Robotics: Using Prior Knowledge about Physical Interaction.
Proceedings of the Robotics: Science and Systems X, 2014


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