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publications
Clustering with Deep Learning: Taxonomy and New Methods
Elie Aljalbout, Vladimir Golkov, Yawar Siddiqui, Maximilian Strobel, and Daniel CremersarXiv, 2018
[ pdf ]
Associative deep clustering: Training a classification network with no labels
Philip Haeusser, Johannes Plapp, Vladimir Golkov, Elie Aljalbout, and Daniel CremersGCPR, 2018
[ pdf ]
Tracking Holistic Object Representations
Axel Sauer*, Elie Aljalbout*, Sami Haddadin (*Shared first authorship)BMVC (oral, acceptance rate: 4%), **Best Science Paper Award**, 2019
[ pdf | url ]
Task-Independent Spiking Central Pattern Generator: A Learning-Based Approach
Elie Aljalbout, Florian Walter, Florian Roehrbein, and Alois KnollNeural Processing Letters, Springer, 2020
[ pdf | url ]
How to Make Deep RL Work in Practice
Nirnai Rao*, Elie Aljalbout*, Axel Sauer*, Sami Haddadin (*Shared first authorship)NeurIPS, Workshop on Deep RL, 2020
[ pdf | url ]
Learning Vision-based Reactive Policies for Obstacle Avoidance
Elie Aljalbout, Ji Chen, Konstantin Ritt, Maximilian Ulmer and Sami HaddadinCoRL, 2020
[ pdf | url ]
Learning robotic manipulation skills using an adaptive force-impedance action space
Maximilian Ulmer, Elie Aljalbout, Sascha Schwarz, Sami HaddadinarXiv, 2021
[ pdf ]
Seeking Visual Discomfort: Curiosity-driven Representations for Reinforcement Learning
E Aljalbout, Maximilian Ulmer, R TriebelICRA, 2022
[ pdf ]
Learning to Centralize Dual-Arm Assembly
Marvin Alles, Elie AljalboutFrontiers in Robotics and AI, 2022
[ pdf ]
CLAS: Coordinating Multi-Robot Manipulation with Central Latent Action Spaces
Elie Aljalbout, Maximilian Karl, Patrick van der SmagtL4DC, 2023
[ pdf ]
talks
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teaching
Robotics and AI: Seminal Work
Seminar course, Technical University of Munich, MSRM, 2019
Robotics Sciences and Systems Intelligence
Seminar course, Technical University of Munich, MSRM, 2019
Fundamentals of Human-centered Robotics
Lecture, Technical University of Munich, MSRM, 2020