Università della Svizzera italiana

Probabilistic models with deep neural networks

Masegosa, Andrés R. ; Cabañas, Rafael ; Langseth, Helge ; Nielsen, Thomas D. ; Salmerón, Antonio

In: Entropy, 2021, vol. 23, no. 1, p. 27 p

Recent advances in statistical inference have significantly expanded the toolbox of probabilistic modeling. Historically, probabilistic modeling has been constrained to very restricted model classes, where exact or approximate probabilistic inference is feasible. However, developments in variational inference, a general form of approximate probabilistic inference that originated in statistical...

Consortium of Swiss Academic Libraries

Dictionary Learning for Fast Classification Based on Soft-thresholding

Fawzi, Alhussein ; Davies, Mike ; Frossard, Pascal

In: International Journal of Computer Vision, 2015, vol. 114, no. 2-3, p. 306-321

Università della Svizzera italiana

Learning structured neural representations for visual reasoning tasks

van Steenkiste, Sjoerd ; Schmidhuber, Jürgen (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2020 ; 2020INFO019.

Deep neural networks learn representations of data to facilitate problem-solving in their respective domains. However, they struggle to acquire a structured representation based on more symbolic entities, which are commonly understood as core abstractions central to human capacity for generalization. This dissertation studies this issue for visual reasoning tasks. Inspired by how humans solve...

Università della Svizzera italiana

New architectures for very deep learning

Srivastava, Rupesh Kumar ; Schmidhuber, Jürgen (Dir.)

Thèse de doctorat : Università della Svizzera italiana, 2018 ; 2018INFO006.

Artificial Neural Networks are increasingly being used in complex real- world applications because many-layered (i.e., deep) architectures can now be trained on large quantities of data. However, training even deeper, and therefore more powerful networks, has hit a barrier due to fundamental limitations in the design of existing networks. This thesis develops new architectures that, for the...

Consortium of Swiss Academic Libraries

Neuroevolution: from architectures to learning

Floreano, Dario ; Dürr, Peter ; Mattiussi, Claudio

In: Evolutionary Intelligence, 2008, vol. 1, no. 1, p. 47-62