Articles with public access mandates - David FilliatLearn more
Available somewhere: 11
Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges
T Lesort, V Lomonaco, A Stoian, D Maltoni, D Filliat, N Díaz-Rodríguez
Information fusion 58, 52-68, 2020
Mandates: European Commission
State representation learning for control: An overview
T Lesort, N Díaz-Rodríguez, JF Goudou, D Filliat
Neural Networks 108, 379-392, 2018
Mandates: European Commission
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case
N Díaz-Rodríguez, A Lamas, J Sanchez, G Franchi, I Donadello, S Tabik, ...
Information Fusion 79, 58-83, 2021
Mandates: Government of Spain
Open-ended learning: a conceptual framework based on representational redescription
S Doncieux, D Filliat, N Díaz-Rodríguez, T Hospedales, R Duro, A Coninx, ...
Frontiers in neurorobotics 12, 59, 2018
Mandates: European Commission
Deep unsupervised state representation learning with robotic priors: a robustness analysis
T Lesort, M Seurin, X Li, N Díaz-Rodríguez, D Filliat
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
Mandates: European Commission
MCA-NMF: Multimodal Concept Acquisition with Non-Negative Matrix Factorization
PYO Olivier Mangin , David Filliat, Louis ten Bosch
PLOS one, 2015
Mandates: European Commission
Real-time distributed receding horizon motion planning and control for mobile multi-robot dynamic systems
JM Mendes Filho, E Lucet, D Filliat
2017 IEEE International Conference on Robotics and Automation (ICRA), 657-663, 2017
Mandates: European Commission
Robotdrlsim: A real time robot simulation platform for reinforcement learning and human interactive demonstration learning
T Sun, L Gong, X Li, S Xie, Z Chen, Q Hu, D Filliat
Journal of Physics: Conference Series 1746 (1), 012035, 2021
Mandates: National Natural Science Foundation of China
Demonstration Guided Actor-Critic Deep Reinforcement Learning for Fast Teaching of Robots in Dynamic Environments
L Gong, T Sun, X Li, K Lin, N Díaz-Rodríguez, D Filliat, Z Zhang, J Zhang
IFAC-PapersOnLine 53 (5), 271-278, 2020
Mandates: National Natural Science Foundation of China
An iterative algorithm for forward-parameterized skill discovery
A Matricon, D Filliat, PY Oudeyer
2016 Joint IEEE International Conference on Development and Learning and …, 2016
Mandates: European Commission
Unsupervised deep learning of state representation using robotic priors
T LESORT, D FILLIAT
Mandates: European Commission
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