High-fidelity parametric gates have been demonstrated with superconducting qubits via rf flux modulation of the qubit frequency. The however leads to renormalization bare qubit-qubit coupling, thereby reducing gate speed. Here, we realize a parametric-resonance gate, which is activated by bringing average frequency modulated in resonance static-frequency while approximately retaining coupling. ...

Abstract In this paper we discuss PyBanshee, which is a Python-based open-source implementation of the MATLAB toolbox BANSHEE. PyBanshee constitutes first fully package to quantify, visualize and validate Non-Parametric Bayesian Networks (NPBNs). The architecture heavily based on its predecessor. It presents full existing tools introduces new modules. Specifically, allows for: (i) choo...

We introduce a new memory architecture for navigation in previously unseen environments, inspired by landmark-based navigation in animals. The proposed semiparametric topological memory (SPTM) consists of a (non-parametric) graph with nodes corresponding to locations in the environment and a (parametric) deep network capable of retrieving nodes from the graph based on observations. The graph st...

Specific colours observed in images of the ocular fundus depend on the architecture of its layers and the optical properties and quantities of any pigments present. These colours can be predicted from the parameters describing the ocular tissue composition using a physics-based model of light transport. This paper reports preliminary results of the application of the inverse process by which th...

This paper presents a novel method for bioprocess hybrid parametric/nonparametric modelling based on mixture of experts (ME) and the Expectation Maximisation (EM) algorithm. The bioreactor system is described by material balance equations whereas the cell population subsystem is described by an adjustable mixture of parametric/nonparametric sub-models inspired in the ME architecture. This idea ...

Speculative multithreading (SpMT) is a thread-level automatic parallelization technique that can accelerate sequential programs, especially for irregular applications that are hard to be parallelized by conventional approaches. Thread partition plays a critical role in SpMT. Conventional machine learning-based thread partition approaches applied machine learning to offline guide partition, but ...

A blind separation problem where the sources are not independent, but have variance dependencies is discussed. For this scenario Hyvärinen and Hurri (2004) proposed an algorithm which requires no assumption on distributions of sources and no parametric model of dependencies between components. In this paper, we extend the semiparametric approach of Amari and Cardoso (1997) to variance dependenc...

In the framework of the on-going SLAM project (Service for Landslide Monitoring), funded by the European Space Agency (ESA) the Permanent Scatterers processing and the analysis of high resolution images (e.g. SPOT5) have been performed at a basin scale, on the whole territory of the Arno River basin (Central Italy). The project aims at the development of a service based on the integration of EO...

In conventional computers, wiring between transistors is required to enable the execution of Boolean logic functions. This has resulted in processors in which billions of transistors are physically interconnected, which limits integration densities, gives rise to huge power consumption and restricts processing speeds. A method to eliminate wiring amongst transistors by condensing Boolean logic ...

We introduce a new memory architecture for navigation in previously unseen environments, inspired by landmark-based navigation in animals. The proposed semiparametric topological memory (SPTM) consists of a (non-parametric) graph with nodes corresponding to locations in the environment and a (parametric) deep network capable of retrieving nodes from the graph based on observations. The graph st...