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2020 – today
- 2024
[j32]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)- [j31]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) - [j30]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) - [e7]Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Noor Sajid, Hideaki Shimazaki, Tim Verbelen, Martijn Wisse:
Active Inference - 4th International Workshop, IWAI 2023, Ghent, Belgium, September 13-15, 2023, Revised Selected Papers. Communications in Computer and Information Science 1915, Springer 2024, ISBN 978-3-031-47957-1 [contents] - [i51]Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Aaron C. Courville, Sai Rajeswar:
Multimodal foundation world models for generalist embodied agents. CoRR abs/2406.18043 (2024) - [i50]Ozan Çatal, Toon Van de Maele, Riddhi J. Pitliya, Mahault Albarracin, Candice Pattisapu, Tim Verbelen:
Belief sharing: a blessing or a curse. CoRR abs/2407.02465 (2024) - [i49]Candice Pattisapu, Tim Verbelen, Riddhi J. Pitliya, Alex B. Kiefer, Mahault Albarracin:
Free Energy in a Circumplex Model of Emotion. CoRR abs/2407.02474 (2024) - [i48]Karl J. Friston, Conor Heins, Tim Verbelen, Lancelot Da Costa, Tommaso Salvatori, Dimitrije Markovic, Alexander Tschantz, Magnus T. Koudahl, Christopher Buckley, Thomas Parr:
From pixels to planning: scale-free active inference. CoRR abs/2407.20292 (2024) - [i47]Daria de Tinguy, Tim Verbelen, Bart Dhoedt:
Exploring and Learning Structure: Active Inference Approach in Navigational Agents. CoRR abs/2408.05982 (2024) - [i46]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) - [i45]Toon Van de Maele, Ozan Çatal, Alexander Tschantz, Christopher L. Buckley, Tim Verbelen:
Variational Bayes Gaussian Splatting. CoRR abs/2410.03592 (2024) - 2023
- [j29]Adnan Albaba, Marc Bauduin, Tim Verbelen, Hichem Sahli, André Bourdoux:
Forward-Looking MIMO-SAR for Enhanced Radar Imaging in Autonomous Mobile Robots. IEEE Access 11: 66934-66948 (2023) - [c44]Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar:
Choreographer: Learning and Adapting Skills in Imagination. ICLR 2023 - [c43]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 - [c42]Ali Safa, Tim Verbelen, Ilja Ocket, André Bourdoux, Hichem Sahli, Francky Catthoor, Georges G. E. Gielen:
Fusing Event-based Camera and Radar for SLAM Using Spiking Neural Networks with Continual STDP Learning. ICRA 2023: 2782-2788 - [c41]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 - [c40]Ali Safa, Tim Verbelen, Lars Keuninckx, Ilja Ocket, André Bourdoux, Francky Catthoor, Georges G. E. Gielen, Gert Cauwenberghs:
Active Inference in Hebbian Learning Networks. IWAI 2023: 239-253 - [e6]Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Noor Sajid, Hideaki Shimazaki, Tim Verbelen:
Active Inference - Third International Workshop, IWAI 2022, Grenoble, France, September 19, 2022, Revised Selected Papers. Communications in Computer and Information Science 1721, Springer 2023, ISBN 978-3-031-28718-3 [contents] - [i44]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) - [i43]Toon Van de Maele, Tim Verbelen, Pietro Mazzaglia, Stefano Ferraro, Bart Dhoedt:
Object-Centric Scene Representations using Active Inference. CoRR abs/2302.03288 (2023) - [i42]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) - [i41]Ali Safa, Tim Verbelen, Lars Keuninckx, Ilja Ocket, André Bourdoux, Francky Catthoor, Georges G. E. Gielen, Gert Cauwenberghs:
Active Inference in Hebbian Learning Networks. CoRR abs/2306.05053 (2023) - [i40]Daria de Tinguy, Toon Van de Maele, Tim Verbelen, Bart Dhoedt:
Inferring Hierarchical Structure in Multi-Room Maze Environments. CoRR abs/2306.13546 (2023) - [i39]Stefano Ferraro, Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt:
FOCUS: Object-Centric World Models for Robotics Manipulation. CoRR abs/2307.02427 (2023) - [i38]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) - [i37]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) - [i36]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) - [i35]Karl J. Friston, Lancelot Da Costa, Alexander Tschantz, Alex B. Kiefer, Tommaso Salvatori, Victorita Neacsu, Magnus T. Koudahl, Conor Heins, Noor Sajid, Dimitrije Markovic, Thomas Parr, Tim Verbelen, Christopher L. Buckley:
Supervised structure learning. CoRR abs/2311.10300 (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) - [i33]Karl J. Friston, Tommaso Salvatori, Takuya Isomura, Alexander Tschantz, Alex B. Kiefer, Tim Verbelen, Magnus T. Koudahl, Aswin Paul, Thomas Parr, Adeel Razi, Brett Kagan, Christopher L. Buckley, Maxwell J. D. Ramstead:
Active Inference and Intentional Behaviour. CoRR abs/2312.07547 (2023) - 2022
- [j28]Peter Kriens, Tim Verbelen:
What Machine Learning Can Learn From Software Modularity. Computer 55(9): 35-42 (2022) - [j27]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) - [j26]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) - [j25]Toon Van de Maele, Tim Verbelen, Ozan Çatal, Bart Dhoedt:
Embodied Object Representation Learning and Recognition. Frontiers Neurorobotics 16: 840658 (2022) - [j24]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) - [j23]Ali Safa, Tim Verbelen, Ilja Ocket, André Bourdoux, Francky Catthoor, Georges G. E. Gielen:
Fail-Safe Human Detection for Drones Using a Multi-Modal Curriculum Learning Approach. IEEE Robotics Autom. Lett. 7(1): 303-310 (2022) - [j22]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) - [c39]Pietro Mazzaglia, Ozan Çatal, Tim Verbelen, Bart Dhoedt:
Curiosity-Driven Exploration via Latent Bayesian Surprise. AAAI 2022: 7752-7760 - [c38]Ozan Çatal, Tim Verbelen, Ni Wang, Matthias Hartmann, Bart Dhoedt:
Bio-inspired monocular drone SLAM. DroneSE/RAPIDO@HiPEAC 2022: 21-26 - [c37]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 - [c36]Daria de Tinguy, Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt:
Home Run: Finding Your Way Home by Imagining Trajectories. IWAI 2022: 210-221 - [c35]Samuel T. Wauthier, Bram Vanhecke, Tim Verbelen, Bart Dhoedt:
Learning Generative Models for Active Inference Using Tensor Networks. IWAI 2022: 285-297 - [c34]Ali Safa, Tim Verbelen, Ilja Ocket, André Bourdoux, Hichem Sahli, Francky Catthoor, Georges G. E. Gielen:
Learning to Encode Vision on the Fly in Unknown Environments: A Continual Learning SLAM Approach for Drones. SSRR 2022: 373-378 - [i32]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) - [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]Ali Safa, Tim Verbelen, Ilja Ocket, André Bourdoux, Hichem Sahli, Francky Catthoor, Georges G. E. Gielen:
Learning to SLAM on the Fly in Unknown Environments: A Continual Learning Approach for Drones in Visually Ambiguous Scenes. CoRR abs/2208.12997 (2022) - [i28]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) - [i27]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) - [i26]Ali Safa, Tim Verbelen, Ilja Ocket, André Bourdoux, Hichem Sahli, Francky Catthoor, Georges G. E. Gielen:
Fusing Event-based Camera and Radar for SLAM Using Spiking Neural Networks with Continual STDP Learning. CoRR abs/2210.04236 (2022) - [i25]Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Alexandre Lacoste, Sai Rajeswar:
Choreographer: Learning and Adapting Skills in Imagination. CoRR abs/2211.13350 (2022) - 2021
- [j21]Joost Verbraeken, Matthijs Wolting, Jonathan Katzy, Jeroen Kloppenburg, Tim Verbelen, Jan S. Rellermeyer:
A Survey on Distributed Machine Learning. ACM Comput. Surv. 53(2): 30:1-30:33 (2021) - [j20]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) - [j19]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) - [j18]Ozan Çatal, Tim Verbelen, Toon Van de Maele, Bart Dhoedt, Adam Safron:
Robot navigation as hierarchical active inference. Neural Networks 142: 192-204 (2021) - [j17]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) - [j16]Ali Safa, Tim Verbelen, Lars Keuninckx, Ilja Ocket, Matthias Hartmann, André Bourdoux, Francky Catthoor, Georges G. E. Gielen:
A Low-Complexity Radar Detector Outperforming OS-CFAR for Indoor Drone Obstacle Avoidance. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 14: 9162-9175 (2021) - [c33]Ozan Çatal, Wouter Jansen, Tim Verbelen, Bart Dhoedt, Jan Steckel:
LatentSLAM: unsupervised multi-sensor representation learning for localization and mapping. ICRA 2021: 6739-6745 - [c32]Cedric De Boom, Samuel Wauthier, Tim Verbelen, Bart Dhoedt:
Dynamic Narrowing of VAE Bottlenecks Using GECO and L0 Regularization. IJCNN 2021: 1-8 - [c31]Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt:
Contrastive Active Inference. NeurIPS 2021: 13870-13882 - [c30]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 - [e5]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I. Communications in Computer and Information Science 1524, Springer 2021, ISBN 978-3-030-93735-5 [contents] - [e4]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II. Communications in Computer and Information Science 1525, Springer 2021, ISBN 978-3-030-93732-4 [contents] - [i24]Pietro Mazzaglia, Ozan Çatal, Tim Verbelen, Bart Dhoedt:
Self-Supervised Exploration via Latent Bayesian Surprise. CoRR abs/2104.07495 (2021) - [i23]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) - [i22]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) - [i21]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) - [i20]Ali Safa, Tim Verbelen, Lars Keuninckx, Ilja Ocket, Matthias Hartmann, André Bourdoux, Francky Catthoor, Georges G. E. Gielen:
A Low-Complexity Radar Detector Outperforming OS-CFAR for Indoor Drone Obstacle Avoidance. CoRR abs/2107.07250 (2021) - [i19]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) - [i18]Ali Safa, Tim Verbelen, Ilja Ocket, André Bourdoux, Francky Catthoor, Georges G. E. Gielen:
Fail-Safe Human Detection for Drones Using a Multi-Modal Curriculum Learning Approach. CoRR abs/2109.13666 (2021) - [i17]Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt:
Contrastive Active Inference. CoRR abs/2110.10083 (2021) - 2020
- [j15]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) - [j14]Sam Leroux, Bert Vankeirsbilck, Tim Verbelen, Pieter Simoens, Bart Dhoedt:
Training binary neural networks with knowledge transfer. Neurocomputing 396: 534-541 (2020) - [j13]Elias De Coninck, Tim Verbelen, Pieter Van Molle, Pieter Simoens, Bart Dhoedt:
Learning robots to grasp by demonstration. Robotics Auton. Syst. 127: 103474 (2020) - [c29]Ozan Çatal, Tim Verbelen, Johannes Nauta, Cedric De Boom, Bart Dhoedt:
Learning Perception and Planning With Deep Active Inference. ICASSP 2020: 3952-3956 - [c28]Ozan Çatal, Sam Leroux, Cedric De Boom, Tim Verbelen, Bart Dhoedt:
Anomaly Detection for Autonomous Guided Vehicles using Bayesian Surprise. IROS 2020: 8148-8153 - [c27]Samuel T. Wauthier, Ozan Çatal, Cedric De Boom, Tim Verbelen, Bart Dhoedt:
Sleep: Model Reduction in Deep Active Inference. IWAI 2020: 72-83 - [c26]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 - [e3]Tim Verbelen, Pablo Lanillos, Christopher L. Buckley, Cedric De Boom:
Active Inference - First International Workshop, IWAI 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14, 2020, Proceedings. Communications in Computer and Information Science 1326, Springer 2020, ISBN 978-3-030-64918-0 [contents] - [i16]Ozan Çatal, Lawrence De Mol, Tim Verbelen, Bart Dhoedt:
Learning to Catch Piglets in Flight. CoRR abs/2001.10220 (2020) - [i15]Ozan Çatal, Tim Verbelen, Johannes Nauta, Cedric De Boom, Bart Dhoedt:
Learning Perception and Planning with Deep Active Inference. CoRR abs/2001.11841 (2020) - [i14]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) - [i13]Ozan Çatal, Samuel Wauthier, Tim Verbelen, Cedric De Boom, Bart Dhoedt:
Deep Active Inference for Autonomous Robot Navigation. CoRR abs/2003.03220 (2020) - [i12]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
- [j12]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) - [c25]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 - [c24]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 - [c23]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 - [i11]Ozan Çatal, Johannes Nauta, Tim Verbelen, Pieter Simoens, Bart Dhoedt:
Bayesian policy selection using active inference. CoRR abs/1904.08149 (2019) - [i10]Peter Kriens, Tim Verbelen:
Software Engineering Practices for Machine Learning. CoRR abs/1906.10366 (2019) - [i9]Joost Verbraeken, Matthijs Wolting, Jonathan Katzy, Jeroen Kloppenburg, Tim Verbelen, Jan S. Rellermeyer:
A Survey on Distributed Machine Learning. CoRR abs/1912.09789 (2019) - 2018
- [j11]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) - [c22]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 - [i8]Sam Leroux, Tim Verbelen, Pieter Simoens, Bart Dhoedt:
Privacy Aware Offloading of Deep Neural Networks. CoRR abs/1805.12024 (2018) - [i7]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) - [i6]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) - [i5]Xander Steenbrugge, Sam Leroux, Tim Verbelen, Bart Dhoedt:
Improving Generalization for Abstract Reasoning Tasks Using Disentangled Feature Representations. CoRR abs/1811.04784 (2018) - 2017
- [j10]Dirk van der Linden, Gert De Sitter, Tim Verbelen, Christof Devriendt, Jan Helsen:
Towards an evolvable data management system for wind turbines. Comput. Stand. Interfaces 51: 87-94 (2017) - [j9]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) - [c21]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 - [i4]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) - [i3]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) - [i2]Sam Leroux, Steven Bohez, Tim Verbelen, Bert Vankeirsbilck, Pieter Simoens, Bart Dhoedt:
Transfer Learning with Binary Neural Networks. CoRR abs/1711.10761 (2017) - 2016
- [j8]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) - [j7]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) - [c20]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 - [c19]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 - [i1]