Speaker: Sergio Segovia Abstract: A brief summary about my lecture, in relation to my doctorate we are exploring the idea of applying the transfer learning technique between the domain of computer vision to the objective of detecting acoustic events. The… Read More
Modeling Uncertainty with Bayesian Neural Networks
Speaker: Sergio Álvarez Abstract: Deep Neural Networks (DNNs) have revolutionized many fields in pattern recognition like speech recognition and object detection. There are, however, some applications in which Neural Networks struggle to offer competitive performance, mainly sensitive ones. These applications… Read More
New loss function to improve calibration with mixup
Speaker: Juan Maroñas Molano Abstract: Deep Neural Networks (DNN) represent the state of the art in many tasks. However, due to their overparameterization, their generalization capabilities are in doubt and still a field under study. Consequently, DNN can overfit and… Read More