Action Recognition with Trajectory-Pooled Deep-Convolutional ...

Le but du module est d'amener les élèves vers une meilleure connaissance de soi pour définir un projet profession- nel, élaborer une stratégie de recherche ...







Deep Reinforcement Learning with Double Q-Learning
Typically, deep RL systems use a deep neural network to compute a non-linear mapping from perceptual inputs to action values (e.g., Mnih et al., 2015) or action ...
Playing Atari with Deep Reinforcement Learning
Efficient exploration remains a major challenge for reinforcement learning. (RL). Common dithering strategies for exploration, such as '-greedy, do.
Deepfake Video Detection Based on Spatial, Spectral, and ...
Our method, TD-MPC, achieves superior sam- ple efficiency and asymptotic performance over prior work on both state and image-based con- tinuous control tasks ...



Autres Cours:

Deep Spatial Autoencoders for Visuomotor Learning