Modeling human target reaching with an adaptive observer implemented with dynamic neural fields FS Fard, P Hollensen, D Heinke, TP Trappenberg Neural Networks 72, 13-30, 2015 | 16 | 2015 |
A novel model for arbitration between planning and habitual control systems FS Fard, TP Trappenberg Frontiers in Neurorobotics - arXiv preprint arXiv:1712.02441, 2017 | 9* | 2017 |
Impact of biased mislabeling on learning with deep networks FS Fard, P Hollensen, S Mcilory, T Trappenberg 2017 International Joint Conference on Neural Networks (IJCNN), 2652-2657, 2017 | 7 | 2017 |
Simulating oculomotor inhibition of return with a two-dimensional dynamic neural field model of the superior colliculus J Satel, FS Fard, Z Wang, TP Trappenberg Australian Journal of Intelligent Information Processing System 14, 27-32, 2014 | 6 | 2014 |
Using Self-Configurable Particle Swarm Optimization for allocation position of rescue robots FSN Fard, H Parvar, ME Shiri, E Soleimani 2010 Second International Conference on Computer and Network Technology, 362-366, 2010 | 6 | 2010 |
Nasil: Neural architecture search with imitation learning FS Fard, A Rad, VS Tomar ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 4 | 2020 |
Mixing habits and planning for multi-step target reaching using arbitrated predictive actor-critic FS Fard, TP Trappenberg 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 3 | 2018 |
An actor critic with an internal model FS Fard, A Nunes, T Trappenberg Annual Conference on Cognitive Computational Neuroscience (CCN), 2017 | 3 | 2017 |
Modelling human target reaching using a novel predictive deep reinforcement learning technique F Sheikhnezhad Fard | 1 | 2018 |
Expediting discovery in Neural Architecture Search by Combining Learning with Planning FS Fard, VS Tomar ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | | 2021 |