Search results for " learning."
showing 10 items of 5179 documents
La DaD nell’emergenza Covid19: restrizione spaziale e sfida per una nuova temporalizzazione
2020
L’introduzione della DaD nell’università, come risposta di emergenza alla pandemia del Covid19, ha comportato inevitabilmente il sacrificio della dimensione spaziale nel percorso formativo degli studenti e nella loro socialità. Questa restrizione, tuttavia, può creare il presupposto per riguadagnare in intensità ciò che si perde in estensione e ripensare, in termini filosofici, il rapporto tra temporalizzazione e spazializzazione nel processo di costruzione della personalità nella sua coscienza storica. The introduction of the DDA in the university, as an emergency response to the Covid19 pandemic, inevitably entailed the sacrifice of the spatial dimension in the training of students and in…
Reinforcement learning approach to nonequilibrium quantum thermodynamics
2021
We use a reinforcement learning approach to reduce entropy production in a closed quantum system brought out of equilibrium. Our strategy makes use of an external control Hamiltonian and a policy gradient technique. Our approach bears no dependence on the quantitative tool chosen to characterize the degree of thermodynamic irreversibility induced by the dynamical process being considered, require little knowledge of the dynamics itself and does not need the tracking of the quantum state of the system during the evolution, thus embodying an experimentally non-demanding approach to the control of non-equilibrium quantum thermodynamics. We successfully apply our methods to the case of single- …
Foreign language learning in multilingual Germany
2021
This special issue on foreign language (FL) learning in multilingual contextsprovides insights into cross- and inter-linguistic phenomena comparingmonolingual and multilingual students who learn FLs in linguistically het-erogeneous classrooms. All contributions are based on data gathered in pro-jects carried out within the research cluster “Language education andmultilingualism”/“Sprachliche Bildung und Mehrsprachigkeit”, which hasbeen funded by the German Federal Ministry for Education and Research(Bundesministerium für Bildung und Forschung, BMBF) from 2013 to 2020. Bybringing together linguistic and educational perspectives on FL learning andteaching as well as different methodological a…
Dynamical learning of a photonics quantum-state engineering process
2021
Abstract. Experimental engineering of high-dimensional quantum states is a crucial task for several quantum information protocols. However, a high degree of precision in the characterization of the noisy experimental apparatus is required to apply existing quantum-state engineering protocols. This is often lacking in practical scenarios, affecting the quality of the engineered states. We implement, experimentally, an automated adaptive optimization protocol to engineer photonic orbital angular momentum (OAM) states. The protocol, given a target output state, performs an online estimation of the quality of the currently produced states, relying on output measurement statistics, and determine…
Towards Open Domain Chatbots—A GRU Architecture for Data Driven Conversations
2018
Understanding of textual content, such as topic and intent recognition, is a critical part of chatbots, allowing the chatbot to provide relevant responses. Although successful in several narrow domains, the potential diversity of content in broader and more open domains renders traditional pattern recognition techniques inaccurate. In this paper, we propose a novel deep learning architecture for content recognition that consists of multiple levels of gated recurrent units (GRUs). The architecture is designed to capture complex sentence structure at multiple levels of abstraction, seeking content recognition for very wide domains, through a distributed scalable representation of content. To …
Monte Carlo Simulations of Au38(SCH3)24 Nanocluster Using Distance-Based Machine Learning Methods
2020
We present an implementation of distance-based machine learning (ML) methods to create a realistic atomistic interaction potential to be used in Monte Carlo simulations of thermal dynamics of thiol...
Elucidating the Influence of the Activation Energy on Reaction Rates by Simulations Based on a Simple Particle Model
2020
An application for visualizing the dynamic properties of an equimolar binary mixture of isotropic reactive particles is presented. By introducing a user selectable choice for the activation energy, the application is useful to demonstrate qualitatively that the reaction rate depends on the above choice and on temperature. The application is based on a 2D realistic dynamic model where atoms move because of their thermal energies and the trajectories are determined by solving numerically Newton’s laws according to a Molecular Dynamics (MD) scheme. Collisions are monitored as time progresses, and every time the collision energy is larger than the selected activation energy, a reactive event oc…
Machine learning regression algorithms for biophysical parameter retrieval: Opportunities for Sentinel-2 and -3
2012
Abstract ESA's upcoming satellites Sentinel-2 (S2) and Sentinel-3 (S3) aim to ensure continuity for Landsat 5/7, SPOT-5, SPOT-Vegetation and Envisat MERIS observations by providing superspectral images of high spatial and temporal resolution. S2 and S3 will deliver near real-time operational products with a high accuracy for land monitoring. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods. Machine learning regression algorithms may be powerful candidates for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. By using data from …
Recent Advances in Techniques for Hyperspectral Image Processing
2009
International audience; Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in less than thirty years from being a sparse research tool into a commodity product available to a broad user community. Currently, there is a need for standardized data processing techniques able to take into account the special properties of hyperspec- tral data. In this paper, we provide a seminal view on recent advances in techniques for hyperspectral image processing. Our main focus is on the design of techniques able to deal with the high-dimensional nature of the data, and to integrate the spa- tial and spectral information. Performance of the discussed techniques is evaluated in …
Statistical retrieval of atmospheric profiles with deep convolutional neural networks
2019
Abstract Infrared atmospheric sounders, such as IASI, provide an unprecedented source of information for atmosphere monitoring and weather forecasting. Sensors provide rich spectral information that allows retrieval of temperature and moisture profiles. From a statistical point of view, the challenge is immense: on the one hand, “underdetermination” is common place as regression needs to work on high dimensional input and output spaces; on the other hand, redundancy is present in all dimensions (spatial, spectral and temporal). On top of this, several noise sources are encountered in the data. In this paper, we present for the first time the use of convolutional neural networks for the retr…