| Year | Title | Author | Publication | Code | Tasks | Notes | Datasets | Notions |
|---|---|---|---|---|---|---|---|---|
| 2021 | Deep ANC: A deep learning approach to active noise control | Zhang and Wang | Neural Networks | - | wideband noise reduction and generalizes well to untrained noises |
Active noise controller, convolutional recurrent network, None, Tra, Hard |
nonlinear distortions,The main idea is to employ deep learning to encode the optimal control parameters corresponding to different noises and environments. | |
| 2021 | Robot navigation as hierarchical active inference | Çatal et al. | Neural Networks | - | Active Inference |
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| 2021 | Bidirectional interaction between visual and motor generative models using Predictive Coding and Active Inference | Annabi et al. | Neural Networks | - | Active Inference |
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| 2021 | Active sensing with artificial neural networks | Solopchuk and Zénon | Neural Networks | - | Active sensing |
gradient-based information gain, Gated Recurrent Unit, None, Tra, Hard |
MNIST | The fitness of behaving agents |
| 2021 | An empirical evaluation of active inference in multi-armed bandits | Marković et al. | Neural Networks | - | Active Inference |
Uncertainty, Bayesian, None, Tra, Hard |
multi-armed bandit problem, a classical task that captures this trade-off, served as a vehicle in machine learning for developing bandit algorithms that proved to be useful in numerous industrial applications. | |
| 2021 | Active inference through whiskers | Mannella et al. | Neural Networks | code | Active inference |
Uncertainty, Bayesian, None, Tra, Hard |
Rodents use whisking to probe actively their environment and to locate objects in space, hence providing a paradigmatic biological example of active sensing. |