b'Tim Verbelen'

research

∙ 09/18/2023

Learning Spatial and Temporal Hierarchies: Hierarchical Active Inference for navigation in Multi-Room Maze Environments

Cognitive maps play a crucial role in facilitating flexible behaviour by...

0 Daria de Tinguy, et al. ∙

research

∙ 08/30/2023

Learning to Navigate from Scratch using World Models and Curiosity: the Good, the Bad, and the Ugly

Learning to navigate unknown environments from scratch is a challenging ...

0 Daria de Tinguy, et al. ∙

research

∙ 08/16/2023

Integrating cognitive map learning and active inference for planning in ambiguous environments

Living organisms need to acquire both cognitive maps for learning the st...

0 Toon Van de Maele, et al. ∙

research

∙ 07/05/2023

FOCUS: Object-Centric World Models for Robotics Manipulation

Understanding the world in terms of objects and the possible interplays ...

0 Stefano Ferraro, et al. ∙

research

∙ 06/23/2023

Inferring Hierarchical Structure in Multi-Room Maze Environments

Cognitive maps play a crucial role in facilitating flexible behaviour by...

0 Daria de Tinguy, et al. ∙

research

∙ 06/08/2023

Active Inference in Hebbian Learning Networks

This work studies how brain-inspired neural ensembles equipped with loca...

0 Ali Safa, et al. ∙

research

∙ 04/14/2023

Symmetry and Complexity in Object-Centric Deep Active Inference Models

Humans perceive and interact with hundreds of objects every day. In doin...

0 Stefano Ferraro, et al. ∙

research

∙ 02/07/2023

Object-Centric Scene Representations using Active Inference

Representing a scene and its constituent objects from raw sensory data i...

0 Toon Van de Maele, et al. ∙

research

∙ 01/06/2023

FMCW Radar Sensing for Indoor Drones Using Learned Representations

Frequency-modulated continuous-wave (FMCW) radar is a promising sensor t...

0 Ali Safa, et al. ∙

research

∙ 11/23/2022

Choreographer: Learning and Adapting Skills in Imagination

Unsupervised skill learning aims to learn a rich repertoire of behaviors...

0 Pietro Mazzaglia, et al. ∙

research

∙ 10/09/2022

Fusing Event-based Camera and Radar for SLAM Using Spiking Neural Networks with Continual STDP Learning

This work proposes a first-of-its-kind SLAM architecture fusing an event...

0 Ali Safa, et al. ∙

research

∙ 09/24/2022

Unsupervised Model-based Pre-training for Data-efficient Control from Pixels

Controlling artificial agents from visual sensory data is an arduous tas...

0 Sai Rajeswar, et al. ∙

research

∙ 09/16/2022

Disentangling Shape and Pose for Object-Centric Deep Active Inference Models

Active inference is a first principles approach for understanding the br...

3 Stefano Ferraro, et al. ∙

research

∙ 08/27/2022

Learning to SLAM on the Fly in Unknown Environments: A Continual Learning Approach for Drones in Visually Ambiguous Scenes

Learning to safely navigate in unknown environments is an important task...

0 Ali Safa, et al. ∙

research

∙ 08/19/2022

Home Run: Finding Your Way Home by Imagining Trajectories

When studying unconstrained behaviour and allowing mice to leave their c...

0 Daria de Tinguy, et al. ∙

research

∙ 08/18/2022

Learning Generative Models for Active Inference using Tensor Networks

Active inference provides a general framework for behavior and learning ...

0 Samuel T. Wauthier, et al. ∙

research

∙ 07/13/2022

The Free Energy Principle for Perception and Action: A Deep Learning Perspective

The free energy principle, and its corollary active inference, constitut...

0 Pietro Mazzaglia, et al. ∙

research

∙ 10/19/2021

Contrastive Active Inference

Active inference is a unifying theory for perception and action resting ...

0 Pietro Mazzaglia, et al. ∙

research

∙ 09/28/2021

Fail-Safe Human Detection for Drones Using a Multi-Modal Curriculum Learning Approach

Drones are currently being explored for safety-critical applications whe...

0 Ali Safa, et al. ∙

research

∙ 08/26/2021

Disentangling What and Where for 3D Object-Centric Representations Through Active Inference

Although modern object detection and classification models achieve high ...

0 Toon Van de Maele, et al. ∙

research

∙ 07/15/2021

A Low-Complexity Radar Detector Outperforming OS-CFAR for Indoor Drone Obstacle Avoidance

As radar sensors are being miniaturized, there is a growing interest for...

0 Ali Safa, et al. ∙

research

∙ 06/17/2021

Towards bio-inspired unsupervised representation learning for indoor aerial navigation

Aerial navigation in GPS-denied, indoor environments, is still an open c...

0 Ni Wang, et al. ∙

research

∙ 05/07/2021

LatentSLAM: unsupervised multi-sensor representation learning for localization and mapping

Biologically inspired algorithms for simultaneous localization and mappi...

0 Ozan Çatal, et al. ∙

research

∙ 04/22/2021

A learning gap between neuroscience and reinforcement learning

Historically, artificial intelligence has drawn much inspiration from ne...

0 Samuel T. Wauthier, et al. ∙

research

∙ 04/15/2021

Self-Supervised Exploration via Latent Bayesian Surprise

Training with Reinforcement Learning requires a reward function that is ...

0 Pietro Mazzaglia, et al. ∙

research

∙ 03/24/2020

Dynamic Narrowing of VAE Bottlenecks Using GECO and L_0 Regularization

When designing variational autoencoders (VAEs) or other types of latent ...

0 Cedric De Boom, et al. ∙

research

∙ 03/06/2020

Deep Active Inference for Autonomous Robot Navigation

Active inference is a theory that underpins the way biological agent's p...

11 Ozan Çatal, et al. ∙

research

∙ 02/21/2020

Rhythm, Chord and Melody Generation for Lead Sheets using Recurrent Neural Networks

Music that is generated by recurrent neural networks often lacks a sense...

0 Cedric De Boom, et al. ∙

research

∙ 01/30/2020

Learning Perception and Planning with Deep Active Inference

Active inference is a process theory of the brain that states that all l...

0 Ozan Çatal, et al. ∙

research

∙ 01/28/2020

Learning to Catch Piglets in Flight

Catching objects in-flight is an outstanding challenge in robotics. In t...

0 Ozan Çatal, et al. ∙

research

∙ 12/20/2019

A Survey on Distributed Machine Learning

The demand for artificial intelligence has grown significantly over the ...

0 Joost Verbraeken, et al. ∙

research

∙ 06/25/2019

Software Engineering Practices for Machine Learning

In the last couple of years we have witnessed an enormous increase of ma...

0 Peter Kriens, et al. ∙

research

∙ 04/17/2019

Bayesian policy selection using active inference

Learning to take actions based on observations is a core requirement for...

0 Ozan Çatal, et al. ∙

research

∙ 11/12/2018

Improving Generalization for Abstract Reasoning Tasks Using Disentangled Feature Representations

In this work we explore the generalization characteristics of unsupervis...

0 Xander Steenbrugge, et al. ∙

research

∙ 09/11/2018

Visualizing Convolutional Neural Networks to Improve Decision Support for Skin Lesion Classification

Because of their state-of-the-art performance in computer vision, CNNs a...

8 Pieter Van Molle, et al. ∙

research

∙ 06/09/2018

Learning to Grasp from a Single Demonstration

Learning-based approaches for robotic grasping using visual sensors typi...

0 Pieter Van Molle, et al. ∙

research

∙ 05/30/2018

Privacy Aware Offloading of Deep Neural Networks

Deep neural networks require large amounts of resources which makes them...

0 Sam Leroux, et al. ∙

research

∙ 11/29/2017

Transfer Learning with Binary Neural Networks

Previous work has shown that it is possible to train deep neural network...

0 Sam Leroux, et al. ∙

research

∙ 08/09/2017

Decoupled Learning of Environment Characteristics for Safe Exploration

Reinforcement learning is a proven technique for an agent to learn a tas...

0 Pieter Van Molle, et al. ∙

research

∙ 03/13/2017

Sensor Fusion for Robot Control through Deep Reinforcement Learning

Deep reinforcement learning is becoming increasingly popular for robot c...

0 Steven Bohez, et al. ∙

research

∙ 05/27/2016

Lazy Evaluation of Convolutional Filters

In this paper we propose a technique which avoids the evaluation of cert...

0 Sam Leroux, et al. ∙

Tim Verbelen

Featured Co-authors