Flexible intentions: An active inference theory M Priorelli, IP Stoianov Frontiers in Computational Neuroscience 17, 1128694, 2023 | 12* | 2023 |
Deep kinematic inference affords efficient and scalable control of bodily movements M Priorelli, G Pezzulo, IP Stoianov Proceedings of the National Academy of Sciences 120 (51), e2309058120, 2023 | 8* | 2023 |
Intention Modulation for Multi-Step Tasks in Continuous Time Active Inference M Priorelli, IP Stoianov Active Inference. IWAI 2022. 1721, 274--284, 2023 | 5 | 2023 |
Active vision in binocular depth estimation: A top-down perspective M Priorelli, G Pezzulo, IP Stoianov Biomimetics 8 (5), 445, 2023 | 4 | 2023 |
Efficient motor learning through action-perception cycles in deep kinematic inference M Priorelli, IP Stoianov International Workshop on Active Inference, 59-70, 2023 | 4 | 2023 |
Slow but flexible or fast but rigid? Discrete and continuous processes compared M Priorelli, IP Stoianov bioRxiv, 2023.08. 20.554008, 2023 | 4 | 2023 |
Dynamic inference by model reduction M Priorelli, IP Stoianov bioRxiv, 2023.09. 10.557043, 2023 | 4 | 2023 |
Modeling motor control in continuous-time Active Inference: a survey M Priorelli, F Maggiore, A Maselli, F Donnarumma, D Maisto, F Mannella, ... IEEE Transactions on Cognitive and Developmental Systems, 2023 | 3 | 2023 |
Neural representation in active inference: Using generative models to interact with—and understand—the lived world G Pezzulo, L D'Amato, F Mannella, M Priorelli, T Van de Maele, ... Annals of the New York Academy of Sciences, 2024 | 1 | 2024 |
Dynamic planning in hierarchical active inference M Priorelli, IP Stoianov arXiv preprint arXiv:2402.11658, 2024 | | 2024 |
Hierarchical hybrid modeling for flexible tool use M Priorelli, IP Stoianov arXiv preprint arXiv:2402.10088, 2024 | | 2024 |