3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.NE2021★ 3 cited
Training Deep Spiking Auto-encoders without Bursting or Dying Neurons through Regularization
Justus F. Hübotter, Pablo Lanillos, Jakub M. Tomczak
Spiking neural networks are a promising approach towards next-generation models of the brain in computational neuroscience. Moreover, compared to classic artificial neural networks…
cs.AI2021
Deep Active Inference for Pixel-Based Discrete Control: Evaluation on the Car Racing Problem
Niels van Hoeffelen, Pablo Lanillos
Despite the potential of active inference for visual-based control, learning the model and the preferences (priors) while interacting with the environment is challenging. Here, we…
cs.RO2021
Robot Localization and Navigation through Predictive Processing using LiDAR
Daniel Burghardt, Pablo Lanillos
Knowing the position of the robot in the world is crucial for navigation. Nowadays, Bayesian filters, such as Kalman and particle-based, are standard approaches in mobile robotics.…