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2020 – today
- 2024
[j121]Daria de Tinguy
, Toon Van de Maele, Tim Verbelen, Bart Dhoedt:
Spatial and Temporal Hierarchy for Autonomous Navigation Using Active Inference in Minigrid Environment. Entropy 26(1): 83 (2024)- [j120]Daria de Tinguy, Tim Verbelen, Bart Dhoedt:
Learning dynamic cognitive map with autonomous navigation. Frontiers Comput. Neurosci. 18 (2024) - [j119]Samuel T. Wauthier, Tim Verbelen, Bart Dhoedt, Bram Vanhecke:
Planning with tensor networks based on active inference. Mach. Learn. Sci. Technol. 5(4): 45012 (2024) - [j118]Toon Van de Maele, Tim Verbelen, Pietro Mazzaglia, Stefano Ferraro, Bart Dhoedt:
Object-Centric Scene Representations Using Active Inference. Neural Comput. 36(4): 677-704 (2024) - [i46]Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Aaron C. Courville, Sai Rajeswar:
Multimodal foundation world models for generalist embodied agents. CoRR abs/2406.18043 (2024) - [i45]Daria de Tinguy, Tim Verbelen, Bart Dhoedt:
Exploring and Learning Structure: Active Inference Approach in Navigational Agents. CoRR abs/2408.05982 (2024) - [i44]Stefano Ferraro, Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Sai Rajeswar:
Representing Positional Information in Generative World Models for Object Manipulation. CoRR abs/2409.12005 (2024) - [i43]Daria de Tinguy, Tim Verbelen, Bart Dhoedt:
Learning Dynamic Cognitive Map with Autonomous Navigation. CoRR abs/2411.08447 (2024) - 2023
- [c194]Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar:
Choreographer: Learning and Adapting Skills in Imagination. ICLR 2023 - [c193]Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron C. Courville, Alexandre Lacoste:
Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels. ICML 2023: 28598-28617 - [c192]Toon Van de Maele, Bart Dhoedt, Tim Verbelen, Giovanni Pezzulo:
Integrating Cognitive Map Learning and Active Inference for Planning in Ambiguous Environments. IWAI 2023: 204-217 - [i42]Ali Safa, Tim Verbelen, Ozan Çatal, Toon Van de Maele, Matthias Hartmann, Bart Dhoedt, André Bourdoux:
FMCW Radar Sensing for Indoor Drones Using Learned Representations. CoRR abs/2301.02451 (2023) - [i41]Toon Van de Maele, Tim Verbelen, Pietro Mazzaglia, Stefano Ferraro, Bart Dhoedt:
Object-Centric Scene Representations using Active Inference. CoRR abs/2302.03288 (2023) - [i40]Stefano Ferraro, Toon Van de Maele, Tim Verbelen, Bart Dhoedt:
Symmetry and Complexity in Object-Centric Deep Active Inference Models. CoRR abs/2304.14493 (2023) - [i39]Daria de Tinguy, Toon Van de Maele, Tim Verbelen, Bart Dhoedt:
Inferring Hierarchical Structure in Multi-Room Maze Environments. CoRR abs/2306.13546 (2023) - [i38]Stefano Ferraro, Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt:
FOCUS: Object-Centric World Models for Robotics Manipulation. CoRR abs/2307.02427 (2023) - [i37]Toon Van de Maele, Bart Dhoedt, Tim Verbelen, Giovanni Pezzulo:
Integrating cognitive map learning and active inference for planning in ambiguous environments. CoRR abs/2308.08307 (2023) - [i36]Daria de Tinguy, Sven Remmery, Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt:
Learning to Navigate from Scratch using World Models and Curiosity: the Good, the Bad, and the Ugly. CoRR abs/2308.15852 (2023) - [i35]Daria de Tinguy, Toon Van de Maele, Tim Verbelen, Bart Dhoedt:
Learning Spatial and Temporal Hierarchies: Hierarchical Active Inference for navigation in Multi-Room Maze Environments. CoRR abs/2309.09864 (2023) - [i34]Daria de Tinguy, Toon Van de Maele, Tim Verbelen, Bart Dhoedt:
Spatial and Temporal Hierarchy for Autonomous Navigation using Active Inference in Minigrid Environment. CoRR abs/2312.05058 (2023) - 2022
- [j117]Pietro Mazzaglia, Tim Verbelen, Ozan Çatal, Bart Dhoedt:
The Free Energy Principle for Perception and Action: A Deep Learning Perspective. Entropy 24(2): 301 (2022) - [j116]Samuel T. Wauthier, Cedric De Boom, Ozan Çatal, Tim Verbelen, Bart Dhoedt:
Model Reduction Through Progressive Latent Space Pruning in Deep Active Inference. Frontiers Neurorobotics 16: 795846 (2022) - [j115]Toon Van de Maele, Tim Verbelen, Ozan Çatal, Bart Dhoedt:
Embodied Object Representation Learning and Recognition. Frontiers Neurorobotics 16: 840658 (2022) - [j114]Sam Leroux, Tim Verbelen, Pieter Simoens, Bart Dhoedt:
Iterative neural networks for adaptive inference on resource-constrained devices. Neural Comput. Appl. 34(13): 10321-10336 (2022) - [j113]Stefano Ferraro, Toon Van de Maele, Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt:
Computational Optimization of Image-Based Reinforcement Learning for Robotics. Sensors 22(19): 7382 (2022) - [c191]Pietro Mazzaglia, Ozan Çatal, Tim Verbelen, Bart Dhoedt:
Curiosity-Driven Exploration via Latent Bayesian Surprise. AAAI 2022: 7752-7760 - [c190]Ozan Çatal, Tim Verbelen, Ni Wang, Matthias Hartmann, Bart Dhoedt:
Bio-inspired monocular drone SLAM. DroneSE/RAPIDO@HiPEAC 2022: 21-26 - [c189]Stefano Ferraro, Toon Van de Maele, Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt:
Disentangling Shape and Pose for Object-Centric Deep Active Inference Models. IWAI 2022: 32-49 - [c188]Daria de Tinguy, Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt:
Home Run: Finding Your Way Home by Imagining Trajectories. IWAI 2022: 210-221 - [c187]Samuel T. Wauthier, Bram Vanhecke, Tim Verbelen, Bart Dhoedt:
Learning Generative Models for Active Inference Using Tensor Networks. IWAI 2022: 285-297 - [i33]Pietro Mazzaglia, Tim Verbelen, Ozan Çatal, Bart Dhoedt:
The Free Energy Principle for Perception and Action: A Deep Learning Perspective. CoRR abs/2207.06415 (2022) - [i32]James Marien, Sam Leroux, Bart Dhoedt, Cedric De Boom:
Audio-guided Album Cover Art Generation with Genetic Algorithms. CoRR abs/2207.07162 (2022) - [i31]Samuel T. Wauthier, Bram Vanhecke, Tim Verbelen, Bart Dhoedt:
Learning Generative Models for Active Inference using Tensor Networks. CoRR abs/2208.08713 (2022) - [i30]Daria de Tinguy, Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt:
Home Run: Finding Your Way Home by Imagining Trajectories. CoRR abs/2208.10914 (2022) - [i29]Stefano Ferraro, Toon Van de Maele, Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt:
Disentangling Shape and Pose for Object-Centric Deep Active Inference Models. CoRR abs/2209.09097 (2022) - [i28]Sai Rajeswar, Pietro Mazzaglia, Tim Verbelen, Alexandre Piché, Bart Dhoedt, Aaron C. Courville, Alexandre Lacoste:
Unsupervised Model-based Pre-training for Data-efficient Control from Pixels. CoRR abs/2209.12016 (2022) - [i27]Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar:
Choreographer: Learning and Adapting Skills in Imagination. CoRR abs/2211.13350 (2022) - 2021
- [j112]Toon Van de Maele, Tim Verbelen, Ozan Çatal, Cedric De Boom, Bart Dhoedt:
Active Vision for Robot Manipulators Using the Free Energy Principle. Frontiers Neurorobotics 15: 642780 (2021) - [j111]Pieter Van Molle, Tim Verbelen, Bert Vankeirsbilck, Jonas De Vylder, Bart Diricx, Tom Kimpe, Pieter Simoens, Bart Dhoedt:
Leveraging the Bhattacharyya coefficient for uncertainty quantification in deep neural networks. Neural Comput. Appl. 33(16): 10259-10275 (2021) - [j110]Ozan Çatal, Tim Verbelen, Toon Van de Maele, Bart Dhoedt, Adam Safron:
Robot navigation as hierarchical active inference. Neural Networks 142: 192-204 (2021) - [j109]Pieter Van Molle, Cedric De Boom, Tim Verbelen, Bert Vankeirsbilck, Jonas De Vylder, Bart Diricx, Pieter Simoens, Bart Dhoedt:
Data-Efficient Sensor Upgrade Path Using Knowledge Distillation. Sensors 21(19): 6523 (2021) - [c186]Ozan Çatal, Wouter Jansen, Tim Verbelen, Bart Dhoedt, Jan Steckel:
LatentSLAM: unsupervised multi-sensor representation learning for localization and mapping. ICRA 2021: 6739-6745 - [c185]Cedric De Boom, Samuel Wauthier, Tim Verbelen, Bart Dhoedt:
Dynamic Narrowing of VAE Bottlenecks Using GECO and L0 Regularization. IJCNN 2021: 1-8 - [c184]Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt:
Contrastive Active Inference. NeurIPS 2021: 13870-13882 - [c183]Toon Van de Maele, Tim Verbelen, Ozan Çatal, Bart Dhoedt:
Disentangling What and Where for 3D Object-Centric Representations Through Active Inference. PKDD/ECML Workshops (1) 2021: 701-714 - [i26]Pietro Mazzaglia, Ozan Çatal, Tim Verbelen, Bart Dhoedt:
Self-Supervised Exploration via Latent Bayesian Surprise. CoRR abs/2104.07495 (2021) - [i25]Samuel T. Wauthier, Pietro Mazzaglia, Ozan Çatal, Cedric De Boom, Tim Verbelen, Bart Dhoedt:
A learning gap between neuroscience and reinforcement learning. CoRR abs/2104.10995 (2021) - [i24]Ozan Çatal, Wouter Jansen, Tim Verbelen, Bart Dhoedt, Jan Steckel:
LatentSLAM: unsupervised multi-sensor representation learning for localization and mapping. CoRR abs/2105.03265 (2021) - [i23]Ni Wang, Ozan Çatal, Tim Verbelen, Matthias Hartmann, Bart Dhoedt:
Towards bio-inspired unsupervised representation learning for indoor aerial navigation. CoRR abs/2106.09326 (2021) - [i22]Toon Van de Maele, Tim Verbelen, Ozan Çatal, Bart Dhoedt:
Disentangling What and Where for 3D Object-Centric Representations Through Active Inference. CoRR abs/2108.11762 (2021) - [i21]Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt:
Contrastive Active Inference. CoRR abs/2110.10083 (2021) - 2020
- [j108]Ozan Çatal, Samuel Wauthier, Cedric De Boom, Tim Verbelen, Bart Dhoedt:
Learning Generative State Space Models for Active Inference. Frontiers Comput. Neurosci. 14: 574372 (2020) - [j107]Sam Leroux, Bert Vankeirsbilck, Tim Verbelen, Pieter Simoens, Bart Dhoedt:
Training binary neural networks with knowledge transfer. Neurocomputing 396: 534-541 (2020) - [j106]Elias De Coninck, Tim Verbelen, Pieter Van Molle, Pieter Simoens, Bart Dhoedt:
Learning robots to grasp by demonstration. Robotics Auton. Syst. 127: 103474 (2020) - [c182]Ozan Çatal, Tim Verbelen, Johannes Nauta, Cedric De Boom, Bart Dhoedt:
Learning Perception and Planning With Deep Active Inference. ICASSP 2020: 3952-3956 - [c181]Ozan Çatal, Sam Leroux, Cedric De Boom, Tim Verbelen, Bart Dhoedt:
Anomaly Detection for Autonomous Guided Vehicles using Bayesian Surprise. IROS 2020: 8148-8153 - [c180]Samuel T. Wauthier, Ozan Çatal, Cedric De Boom, Tim Verbelen, Bart Dhoedt:
Sleep: Model Reduction in Deep Active Inference. IWAI 2020: 72-83 - [c179]Toon Van de Maele, Tim Verbelen, Ozan Çatal, Cedric De Boom, Bart Dhoedt:
You Only Look as Much as You Have To - Using the Free Energy Principle for Active Vision. IWAI 2020: 92-100 - [i20]Ozan Çatal, Lawrence De Mol, Tim Verbelen, Bart Dhoedt:
Learning to Catch Piglets in Flight. CoRR abs/2001.10220 (2020) - [i19]Ozan Çatal, Tim Verbelen, Johannes Nauta, Cedric De Boom, Bart Dhoedt:
Learning Perception and Planning with Deep Active Inference. CoRR abs/2001.11841 (2020) - [i18]Cedric De Boom, Stephanie Van Laere, Tim Verbelen, Bart Dhoedt:
Rhythm, Chord and Melody Generation for Lead Sheets using Recurrent Neural Networks. CoRR abs/2002.10266 (2020) - [i17]Ozan Çatal, Samuel Wauthier, Tim Verbelen, Cedric De Boom, Bart Dhoedt:
Deep Active Inference for Autonomous Robot Navigation. CoRR abs/2003.03220 (2020) - [i16]Cedric De Boom, Samuel Wauthier, Tim Verbelen, Bart Dhoedt:
Dynamic Narrowing of VAE Bottlenecks Using GECO and L0 Regularization. CoRR abs/2003.10901 (2020)
2010 – 2019
- 2019
- [j105]Amirreza Yousefzadeh, Teresa Serrano-Gotarredona, Bernabé Linares-Barranco, Mina A. Khoei, Sahar Hosseini, Priscila C. Holanda, Sam Leroux, Orlando Moreira, Jonathan Tapson, Bart Dhoedt, Pieter Simoens:
Asynchronous Spiking Neurons, the Natural Key to Exploit Temporal Sparsity. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(4): 668-678 (2019) - [j104]Sam Leroux, Steven Bohez, Elias De Coninck, Pieter Van Molle, Bert Vankeirsbilck, Tim Verbelen, Pieter Simoens, Bart Dhoedt:
Multi-fidelity deep neural networks for adaptive inference in the internet of multimedia things. Future Gener. Comput. Syst. 97: 355-360 (2019) - [j103]Cedric De Boom, Thomas Demeester, Bart Dhoedt:
Character-level recurrent neural networks in practice: comparing training and sampling schemes. Neural Comput. Appl. 31(8): 4001-4017 (2019) - [c178]Amirreza Yousefzadeh, Sahar Hosseini, Priscila C. Holanda, Sam Leroux, Thilo Werner, Teresa Serrano-Gotarredona, Bernabé Linares-Barranco, Bart Dhoedt, Pieter Simoens:
Conversion of Synchronous Artificial Neural Network to Asynchronous Spiking Neural Network using sigma-delta quantization. AICAS 2019: 81-85 - [c177]Elias De Coninck, Tim Verbelen, Pieter Van Molle, Pieter Simoens, Bart Dhoedt:
Learning to Grasp Arbitrary Household Objects from a Single Demonstration. IROS 2019: 2372-2377 - [c176]Pieter Van Molle, Tim Verbelen, Cedric De Boom, Bert Vankeirsbilck, Jonas De Vylder, Bart Diricx, Tom Kimpe, Pieter Simoens, Bart Dhoedt:
Quantifying Uncertainty of Deep Neural Networks in Skin Lesion Classification. UNSURE/CLIP@MICCAI 2019: 52-61 - [c175]Cedric De Boom, Stephanie Van Laere, Tim Verbelen, Bart Dhoedt:
Rhythm, Chord and Melody Generation for Lead Sheets Using Recurrent Neural Networks. PKDD/ECML Workshops (2) 2019: 454-461 - [i15]Ozan Çatal, Johannes Nauta, Tim Verbelen, Pieter Simoens, Bart Dhoedt:
Bayesian policy selection using active inference. CoRR abs/1904.08149 (2019) - 2018
- [j102]Elias De Coninck, Steven Bohez, Sam Leroux, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt:
DIANNE: a modular framework for designing, training and deploying deep neural networks on heterogeneous distributed infrastructure. J. Syst. Softw. 141: 52-65 (2018) - [j101]Steven Bohez, Glenn Daneels, Lander Van Herzeele, Niels Van Kets, Sam Decrock, Matthias De Geyter, Glenn Van Wallendael, Peter Lambert, Bart Dhoedt, Pieter Simoens, Steven Latré, Jeroen Famaey:
The crowd as a cameraman: on-stage display of crowdsourced mobile video at large-scale events. Multim. Tools Appl. 77(1): 597-629 (2018) - [j100]Steven Van Canneyt, Philip Leroux, Bart Dhoedt, Thomas Demeester:
Modeling and predicting the popularity of online news based on temporal and content-related features. Multim. Tools Appl. 77(1): 1409-1436 (2018) - [j99]Cedric De Boom, Rohan Agrawal, Samantha Hansen, Esh Kumar, Romain Yon, Ching-Wei Chen, Thomas Demeester, Bart Dhoedt:
Large-scale user modeling with recurrent neural networks for music discovery on multiple time scales. Multim. Tools Appl. 77(12): 15385-15407 (2018) - [j98]Piet Smet, Bart Dhoedt, Pieter Simoens:
Docker Layer Placement for On-Demand Provisioning of Services on Edge Clouds. IEEE Trans. Netw. Serv. Manag. 15(3): 1161-1174 (2018) - [c174]Sam Leroux, Pavlo Molchanov, Pieter Simoens, Bart Dhoedt, Thomas M. Breuel, Jan Kautz:
IamNN: Iterative and Adaptive Mobile Neural Network for efficient image classification. ICLR (Workshop) 2018 - [c173]Pieter Van Molle, Miguel De Strooper, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt:
Visualizing Convolutional Neural Networks to Improve Decision Support for Skin Lesion Classification. MLCN/DLF/iMIMIC@MICCAI 2018: 115-123 - [c172]Sam Leroux, Steven Bohez, Pieter-Jan Maenhaut, Nathan Meheus, Pieter Simoens, Bart Dhoedt:
Fingerprinting encrypted network traffic types using machine learning. NOMS 2018: 1-5 - [i14]Cedric De Boom, Thomas Demeester, Bart Dhoedt:
Character-level Recurrent Neural Networks in Practice: Comparing Training and Sampling Schemes. CoRR abs/1801.00632 (2018) - [i13]Sam Leroux, Pavlo Molchanov, Pieter Simoens, Bart Dhoedt, Thomas M. Breuel, Jan Kautz:
IamNN: Iterative and Adaptive Mobile Neural Network for Efficient Image Classification. CoRR abs/1804.10123 (2018) - [i12]Sam Leroux, Tim Verbelen, Pieter Simoens, Bart Dhoedt:
Privacy Aware Offloading of Deep Neural Networks. CoRR abs/1805.12024 (2018) - [i11]Pieter Van Molle, Tim Verbelen, Elias De Coninck, Cedric De Boom, Pieter Simoens, Bart Dhoedt:
Learning to Grasp from a Single Demonstration. CoRR abs/1806.03486 (2018) - [i10]Pieter Van Molle, Miguel De Strooper, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt:
Visualizing Convolutional Neural Networks to Improve Decision Support for Skin Lesion Classification. CoRR abs/1809.03851 (2018) - [i9]Xander Steenbrugge, Sam Leroux, Tim Verbelen, Bart Dhoedt:
Improving Generalization for Abstract Reasoning Tasks Using Disentangled Feature Representations. CoRR abs/1811.04784 (2018) - 2017
- [j97]Sam Leroux, Steven Bohez, Elias De Coninck, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt:
The cascading neural network: building the Internet of Smart Things. Knowl. Inf. Syst. 52(3): 791-814 (2017) - [c171]Steven Bohez, Tim Verbelen, Elias De Coninck, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt:
Sensor fusion for robot control through deep reinforcement learning. IROS 2017: 2365-2370 - [i8]Steven Bohez, Tim Verbelen, Elias De Coninck, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt:
Sensor Fusion for Robot Control through Deep Reinforcement Learning. CoRR abs/1703.04550 (2017) - [i7]Pieter Van Molle, Tim Verbelen, Steven Bohez, Sam Leroux, Pieter Simoens, Bart Dhoedt:
Decoupled Learning of Environment Characteristics for Safe Exploration. CoRR abs/1708.02838 (2017) - [i6]Cedric De Boom, Rohan Agrawal, Samantha Hansen, Esh Kumar, Romain Yon, Ching-Wei Chen, Thomas Demeester, Bart Dhoedt:
Large-Scale User Modeling with Recurrent Neural Networks for Music Discovery on Multiple Time Scales. CoRR abs/1708.06520 (2017) - [i5]Sam Leroux, Steven Bohez, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt:
Transfer Learning with Binary Neural Networks. CoRR abs/1711.10761 (2017) - 2016
- [j96]Niels Sluijs, Tim Wauters, Chris Develder, Filip De Turck, Piet Demeester, Bart Dhoedt:
Using topology information for quality-aware Peer-to-Peer multilayer video streaming. Int. J. Commun. Syst. 29(10): 1620-1644 (2016) - [j95]Steven Van Canneyt, Steven Schockaert, Bart Dhoedt:
Categorizing events using spatio-temporal and user features from Flickr. Inf. Sci. 328: 76-96 (2016) - [j94]Farhan Azmat Ali, Pieter Simoens, Tim Verbelen, Piet Demeester, Bart Dhoedt:
Mobile device power models for energy efficient dynamic offloading at runtime. J. Syst. Softw. 113: 173-187 (2016) - [j93]Elias De Coninck, Tim Verbelen, Bert Vankeirsbilck, Steven Bohez, Pieter Simoens, Bart Dhoedt:
Dynamic auto-scaling and scheduling of deadline constrained service workloads on IaaS clouds. J. Syst. Softw. 118: 101-114 (2016) - [j92]Peter Quax, Jori Liesenborgs, Arno Barzan, Martijn Croonen, Wim Lamotte, Bert Vankeirsbilck, Bart Dhoedt, Tom Kimpe, Kurt Pattyn, Matthew McLin:
Remote rendering solutions using web technologies. Multim. Tools Appl. 75(8): 4383-4410 (2016) - [j91]Cedric De Boom, Steven Van Canneyt, Thomas Demeester, Bart Dhoedt:
Representation learning for very short texts using weighted word embedding aggregation. Pattern Recognit. Lett. 80: 150-156 (2016) - [c170]Elias De Coninck, Steven Bohez, Sam Leroux, Tim Verbelen, Bert Vankeirsbilck, Bart Dhoedt, Pieter Simoens:
Middleware Platform for Distributed Applications Incorporating Robots, Sensors and the Cloud. CloudNet 2016: 218-223 - [c169]Sam Leroux, Steven Bohez, Elias De Coninck, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt:
Multi-fidelity matryoshka neural networks for constrained IoT devices. IJCNN 2016: 1305-1309 - [c168]Hendrik Moens, Bart Dhoedt, Filip De Turck:
Management of customizable Software-as-a-Service in cloud and network environments. NOMS 2016: 955-960 - [c167]Piet Smet, Bart Dhoedt, Pieter Simoens:
On-demand provisioning of long-tail services in distributed clouds. NOMS 2016: 1320-1323 - [c166]Piet Smet, Bart Dhoedt, Pieter Simoens:
QuLa: Service Selection and Forwarding Table Population in Service-Centric Networking Using Real-Life Topologies. PDP 2016: 58-65 - [i4]Cedric De Boom, Sam Leroux, Steven Bohez, Pieter Simoens, Thomas Demeester, Bart Dhoedt:
Efficiency Evaluation of Character-level RNN Training Schedules. CoRR abs/1605.02486 (2016) - [i3]Sam Leroux, Steven Bohez, Cedric De Boom, Elias De Coninck, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt:
Lazy Evaluation of Convolutional Filters. CoRR abs/1605.08543 (2016) - [i2]Cedric De Boom, Steven Van Canneyt, Thomas Demeester, Bart Dhoedt:
Representation learning for very short texts using weighted word embedding aggregation. CoRR abs/1607.00570 (2016) - 2015
- [j90]Dieter De Witte, Jan Van de Velde, Dries Decap, Michiel Van Bel, Pieter Audenaert, Piet Demeester, Bart Dhoedt, Klaas Vandepoele, Jan Fostier:
BLSSpeller: exhaustive comparative discovery of conserved cis-regulatory elements. Bioinform. 31(23): 3758-3766 (2015) - [j89]Hendrik Moens, Bart Dhoedt, Filip De Turck:
Allocating resources for customizable multi-tenant applications in clouds using dynamic feature placement. Future Gener. Comput. Syst. 53: 63-76 (2015) - [j88]Piet Smet, Pieter Simoens, Bart Dhoedt:
QuLa: Queue and latency-aware service selection and routing in service-centric networking. J. Commun. Networks 17(3): 306-320 (2015) - [j87]Steven Bohez, Tim Verbelen, Pieter Simoens, Bart Dhoedt:
Discrete-event simulation for efficient and stable resource allocation in collaborative mobile cloudlets. Simul. Model. Pract. Theory 50: 109-129 (2015) - [c165]Steven Van Canneyt, Nathan Claeys, Bart Dhoedt:
Topic-Dependent Sentiment Classification on Twitter. ECIR 2015: 441-446 - [c164]Steven Bohez, Elias De Coninck, Tim Verbelen, Bart Dhoedt:
Androsgi: bringing the power of OSGi to Android. ETX 2015: 1-6 - [c163]Cedric De Boom, Steven Van Canneyt, Steven Bohez, Thomas Demeester, Bart Dhoedt:
Learning Semantic Similarity for Very Short Texts. ICDM Workshops 2015: 1229-1234 - [c162]