Elie Aljalbout

Orcid: 0000-0003-0590-0043

According to our database1, Elie Aljalbout authored at least 18 papers between 2018 and 2024.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2024
On the Role of the Action Space in Robot Manipulation Learning and Sim-to-Real Transfer.
IEEE Robotics Autom. Lett., June, 2024

LIMT: Language-Informed Multi-Task Visual World Models.
CoRR, 2024

The Shortcomings of Force-from-Motion in Robot Learning.
CoRR, 2024

Guided Decoding for Robot Motion Generation and Adaption.
CoRR, 2024

Guided Decoding for Robot On-line Motion Generation and Adaption.
Proceedings of the 23rd IEEE-RAS International Conference on Humanoid Robots, 2024

2023
Editorial: Language, affordance and physics in robot cognition and intelligent systems.
Frontiers Robotics AI, 2023

CLAS: Coordinating Multi-Robot Manipulation with Central Latent Action Spaces.
Proceedings of the Learning for Dynamics and Control Conference, 2023

2022
Learning to Centralize Dual-Arm Assembly.
Frontiers Robotics AI, 2022

Seeking Visual Discomfort: Curiosity-driven Representations for Reinforcement Learning.
Proceedings of the 2022 International Conference on Robotics and Automation, 2022

2021
Learning Robotic Manipulation Skills Using an Adaptive Force-Impedance Action Space.
CoRR, 2021

Making Curiosity Explicit in Vision-based RL.
CoRR, 2021

Dual-Arm Adversarial Robot Learning.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020
Task-Independent Spiking Central Pattern Generator: A Learning-Based Approach.
Neural Process. Lett., 2020

How to Make Deep RL Work in Practice.
CoRR, 2020

Learning Vision-based Reactive Policies for Obstacle Avoidance.
Proceedings of the 4th Conference on Robot Learning, 2020

2019
Tracking Holistic Object Representations.
Proceedings of the 30th British Machine Vision Conference 2019, 2019

2018
Clustering with Deep Learning: Taxonomy and New Methods.
CoRR, 2018

Associative Deep Clustering: Training a Classification Network with No Labels.
Proceedings of the Pattern Recognition - 40th German Conference, 2018


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