790 citations · 2k across the 26 of their papers we have counts for
27 papers
Representing Signs as Signs: One-Shot ISLR to Facilitate Functional Sign Language Technologies
Toon Vandendriessche, Mathieu De Coster, Annelies Lejon +1
Isolated Sign Language Recognition (ISLR) is crucial for scalable sign language technology, yet language-specific approaches limit current models. To address this, we propose a one…
Word Synchronization Challenge: A Benchmark for Word Association Responses for Large Language Models
Tanguy Cazalets, Joni Dambre
This paper introduces the Word Synchronization Challenge, a novel benchmark to evaluate large language models (LLMs) in Human-Computer Interaction (HCI). This benchmark uses a dyna…
Learned Thresholds Token Merging and Pruning for Vision Transformers
Maxim Bonnaerens, Joni Dambre
Vision transformers have demonstrated remarkable success in a wide range of computer vision tasks over the last years. However, their high computational costs remain a significant…
Integrated Photonic Reservoir Computing with All-Optical Readout
Chonghuai Ma, Joris Van Kerrebrouck, Hong Deng +5
Integrated photonic reservoir computing has been demonstrated to be able to tackle different problems because of its neural network nature. A key advantage of photonic reservoir co…
Towards the extraction of robust sign embeddings for low resource sign language recognition
Mathieu De Coster, Ellen Rushe, Ruth Holmes +2
Isolated Sign Language Recognition (SLR) has mostly been applied on datasets containing signs executed slowly and clearly by a limited group of signers. In real-world scenarios, ho…
Hardware-aware mobile building block evaluation for computer vision
Maxim Bonnaerens, Matthias Freiberger, Marian Verhelst +1
In this work we propose a methodology to accurately evaluate and compare the performance of efficient neural network building blocks for computer vision in a hardware-aware manner.…
Machine Translation from Signed to Spoken Languages: State of the Art and Challenges
Mathieu De Coster, Dimitar Shterionov, Mieke Van Herreweghe +1
Automatic translation from signed to spoken languages is an interdisciplinary research domain, lying on the intersection of computer vision, machine translation and linguistics. Ne…
Modeling electronic response properties with an explicit-electron machine learning potential
Maarten Cools-Ceuppens, Joni Dambre, Toon Verstraelen
Explicit-electron force fields introduce electrons or electron pairs as semi-classical particles in force fields or empirical potentials, which are suitable for molecular dynamics…
Anchor Pruning for Object Detection
Maxim Bonnaerens, Matthias Freiberger, Joni Dambre
This paper proposes anchor pruning for object detection in one-stage anchor-based detectors. While pruning techniques are widely used to reduce the computational cost of convolutio…
PyTorch-Hebbian: facilitating local learning in a deep learning framework
Jules Talloen, Joni Dambre, Alexander Vandesompele
Recently, unsupervised local learning, based on Hebb's idea that change in synaptic efficacy depends on the activity of the pre- and postsynaptic neuron only, has shown potential a…
Populations of Spiking Neurons for Reservoir Computing: Closed Loop Control of a Compliant Quadruped
Alexander Vandesompele, Gabriel Urbain, Francis wyffels +1
Compliant robots can be more versatile than traditional robots, but their control is more complex. The dynamics of compliant bodies can however be turned into an advantage using th…
Stance Control Inspired by Cerebellum Stabilizes Reflex-Based Locomotion on HyQ Robot
Gabriel Urbain, Victor Barasuol, Claudio Semini +2
Advances in legged robotics are strongly rooted in animal observations. A clear illustration of this claim is the generalization of Central Pattern Generators (CPG), first identifi…
Towards Deep Physical Reservoir Computing Through Automatic Task Decomposition And Mapping
Matthias Freiberger, Peter Bienstman, Joni Dambre
Photonic reservoir computing is a promising candidate for low-energy computing at high bandwidths. Despite recent successes, there are bounds to what one can achieve simply by maki…
Addressing Limited Weight Resolution in a Fully Optical Neuromorphic Reservoir Computing Readout
Chonghuai Ma, Floris Laporte, Joni Dambre +1
Using optical hardware for neuromorphic computing has become more and more popular recently due to its efficient high-speed data processing capabilities and low power consumption.…
Training Passive Photonic Reservoirs with Integrated Optical Readout
Matthias Freiberger, Andrew Katumba, Peter Bienstman +1
As Moore's law comes to an end, neuromorphic approaches to computing are on the rise. One of these, passive photonic reservoir computing, is a strong candidate for computing at hig…
Explaining Character-Aware Neural Networks for Word-Level Prediction: Do They Discover Linguistic Rules?
Fréderic Godin, Kris Demuynck, Joni Dambre +2
Character-level features are currently used in different neural network-based natural language processing algorithms. However, little is known about the character-level patterns th…
BRUNO: A Deep Recurrent Model for Exchangeable Data
Iryna Korshunova, Jonas Degrave, Ferenc Huszár +3
We present a novel model architecture which leverages deep learning tools to perform exact Bayesian inference on sets of high dimensional, complex observations. Our model is provab…
Improving Language Modeling using Densely Connected Recurrent Neural Networks
Fréderic Godin, Joni Dambre, Wesley De Neve
In this paper, we introduce the novel concept of densely connected layers into recurrent neural networks. We evaluate our proposed architecture on the Penn Treebank language modeli…
Dual Rectified Linear Units (DReLUs): A Replacement for Tanh Activation Functions in Quasi-Recurrent Neural Networks
Fréderic Godin, Jonas Degrave, Joni Dambre +1
In this paper, we introduce a novel type of Rectified Linear Unit (ReLU), called a Dual Rectified Linear Unit (DReLU). A DReLU, which comes with an unbounded positive and negative…
Fast Face-swap Using Convolutional Neural Networks
Iryna Korshunova, Wenzhe Shi, Joni Dambre +1
We consider the problem of face swapping in images, where an input identity is transformed into a target identity while preserving pose, facial expression, and lighting. To perform…
A Differentiable Physics Engine for Deep Learning in Robotics
Jonas Degrave, Michiel Hermans, Joni Dambre +1
An important field in robotics is the optimization of controllers. Currently, robots are often treated as a black box in this optimization process, which is the reason why derivati…
Beyond Temporal Pooling: Recurrence and Temporal Convolutions for Gesture Recognition in Video
Lionel Pigou, Aäron van den Oord, Sander Dieleman +2
Recent studies have demonstrated the power of recurrent neural networks for machine translation, image captioning and speech recognition. For the task of capturing temporal structu…
Rotation-invariant convolutional neural networks for galaxy morphology prediction
Sander Dieleman, Kyle W. Willett, Joni Dambre
Measuring the morphological parameters of galaxies is a key requirement for studying their formation and evolution. Surveys such as the Sloan Digital Sky Survey (SDSS) have resulte…
Photonic Delay Systems as Machine Learning Implementations
Michiel Hermans, Miguel Soriano, Joni Dambre +2
Nonlinear photonic delay systems present interesting implementation platforms for machine learning models. They can be extremely fast, offer great degrees of parallelism and potent…