A Survey on Bayesian Deep Learning

A comprehensive artificial intelligence system needs to not only perceive the environment with different `senses' (e.g., seeing and hearing) but also infer the world's conditional (or even causal) relations and corresponding uncertainty. The past decade has seen major advances in many perception tasks such as visual object recognition and speech recognition using deep learning models. For higher-level inference, however, probabilistic graphical models with their Bayesian nature are still more powerful and flexible. In recent years, Bayesian deep learning has emerged as a unified probabilistic framework to tightly integrate deep learning and Bayesian models. In this general framework, the perception of text or images using deep learning can boost the performance of higher-level inference and in turn, the feedback from the inference process is able to enhance the perception of text or images. This survey provides a comprehensive introduction to Bayesian deep learning and reviews its recent applications on recommender systems, topic models, control, etc. Besides, we also discuss the relationship and differences between Bayesian deep learning and other related topics such as Bayesian treatment of neural networks.Comment: To appear in ACM Computing Surveys (CSUR) 202

Cable-Driven Robots with Wireless Control Capability for Pedagogical Illustration in Science

Science teaching in secondary schools is often abstract for students. Even if some experiments can be conducted in classrooms, mainly for chemistry or some physics fields, mathematics is not an experimental science. Teachers have to convince students that theorems have practical implications. We present teachers an original and easy-to-use pedagogical tool: a cable-driven robot with a Web-based remote control interface. The robot implements several scientific concepts such as 3D-geometry and kinematics. The remote control enables the teacher to move freely in the classroom.Comment: CAR - 8th National Conference on "Control Architecure of Robots" (2013

Marine Protected Areas and commercial fisheries: the existing fishery in potential protected areas, and a modelling study of the impact of protected areas on North Sea Plaice

Dit rapport presenteert resultaten van onderzoek, dat in 2005/2006 is uitgevoerd. In het kader van de Europese Vogel en Habitat Richtlijnen dienen lidstaten te beschermen gebieden op zee aan te wijzen, wat mogelijk zou leiden tot beperkingen van visserijactiviteiten in deze gebieden. De vraag was, welke invloed dit zou hebben op de vis en visserij. In dit onderzoek is enerzijds een statische beschrijving opgesteld van de visserijinspanning en de vangsten in de voorgestelde gebieden, en is anderzijds een eerste analyse (simulatie-model) opgezet van het lange-termijn effect op migrerende vis (schol). Dit onderzoek werd eind 2006 afgerond met een concept-rapport