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Featured Co-authors

Tadahiro Taniguchi
51 publications
Tamim Asfour
33 publications
Matej Hoffmann
29 publications
Aykut Erdem
28 publications
Erkut Erdem
28 publications
Benjamin Rosman
26 publications
Pablo Lanillos
23 publications
Justus Piater
18 publications
Florentin Wörgötter
18 publications
Masahiro Suzuki
14 publications
Dimitri Ognibene
13 publications

∙ 09/19/2023

Multi-Object Graph Affordance Network: Enabling Goal-Oriented Planning through Compound Object Affordances

Learning object affordances is an effective tool in the field of robot l...

0 Tuba Girgin, et al. ∙

∙ 09/02/2023

Developmental Scaffolding with Large Language Models

Exploratoration and self-observation are key mechanisms of infant sensor...

0 Batuhan Celik, et al. ∙

∙ 09/02/2023

Discovering Predictive Relational Object Symbols with Symbolic Attentive Layers

In this paper, we propose and realize a new deep learning architecture f...

0 Alper Ahmetoğlu, et al. ∙

∙ 07/10/2023

Diffusion Policies for Out-of-Distribution Generalization in Offline Reinforcement Learning

Offline Reinforcement Learning (RL) methods leverage previous experience...

1 Suzan Ece Ada, et al. ∙

∙ 03/16/2023

Multi-step planning with learned effects of (possibly partial) action executions

In this paper, we propose an affordance model, which is built on Conditi...

0 Utku Bozdogan, et al. ∙

∙ 02/20/2023

Meta-World Conditional Neural Processes

We propose Meta-World Conditional Neural Processes (MW-CNP), a condition...

12 Suzan Ece Ada, et al. ∙

∙ 01/14/2023

World Models and Predictive Coding for Cognitive and Developmental Robotics: Frontiers and Challenges

Creating autonomous robots that can actively explore the environment, ac...

19 Tadahiro Taniguchi, et al. ∙

∙ 10/07/2022

Learning Social Navigation from Demonstrations with Conditional Neural Processes

Sociability is essential for modern robots to increase their acceptabili...

0 Yigit Yildirim, et al. ∙

∙ 09/28/2022

Bimanual rope manipulation skill synthesis through context dependent correction policy learning from human demonstration

Learning from demonstration (LfD) provides a convenient means to equip r...

0 T. Baturhan Akbulut, et al. ∙

∙ 08/01/2022

Learning Multi-Object Symbols for Manipulation with Attentive Deep Effect Predictors

In this paper, we propose a concept learning architecture that enables a...

0 Alper Ahmetoğlu, et al. ∙

∙ 06/18/2021

High-level Features for Resource Economy and Fast Learning in Skill Transfer

Abstraction is an important aspect of intelligence which enables agents ...

0 Alper Ahmetoğlu, et al. ∙

∙ 02/03/2021

Object and Relation Centric Representations for Push Effect Prediction

Pushing is an essential non-prehensile manipulation skill used for tasks...

0 Ahmet E. Tekden, et al. ∙

∙ 12/04/2020

DeepSym: Deep Symbol Generation and Rule Learning from Unsupervised Continuous Robot Interaction for Planning

Autonomous discovery of discrete symbols and rules from continuous inter...

30 Alper Ahmetoğlu, et al. ∙

∙ 11/09/2020

Reward Conditioned Neural Movement Primitives for Population Based Variational Policy Optimization

The aim of this paper is to study the reward based policy exploration pr...

0 M. Tuluhan Akbulut, et al. ∙

∙ 08/26/2020

Intrinsic Motivation in Object-Action-Outcome Blending Latent Space

One effective approach for equipping artificial agents with sensorimotor...

0 Melisa Sener, et al. ∙

∙ 07/26/2020

Trick the Body Trick the Mind: Avatar representation affects the perception of available action possibilities in Virtual Reality

In immersive Virtual Reality (VR), your brain can trick you into believi...

0 Tugce Akkoc, et al. ∙

∙ 07/23/2020

Time Perception: A Review on Psychological, Computational and Robotic Models

Animals exploit time to survive in the world. Temporal information is re...

0 Hamit Basgol, et al. ∙

∙ 03/25/2020

Adaptive Conditional Neural Movement Primitives via Representation Sharing Between Supervised and Reinforcement Learning

Learning by Demonstration provides a sample efficient way to equip robot...

0 M. Tuluhan Akbulut, et al. ∙

∙ 09/09/2019

Belief Regulated Dual Propagation Nets for Learning Action Effects on Articulated Multi-Part Objects

In recent years, graph neural networks have been successfully applied fo...

0 Ahmet E. Tekden, et al. ∙

∙ 09/03/2019

Generalization in Transfer Learning

Agents trained with deep reinforcement learning algorithms are capable o...

39 Suzan Ece Ada, et al. ∙

∙ 01/26/2018

Symbol Emergence in Cognitive Developmental Systems: a Survey

Symbol emergence through a robot's own interactive exploration of the wo...

0 Tadahiro Taniguchi, et al. ∙

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