Publication

Reconstruction From Multiple Poses in Fluorescence Imaging: Proof of Concept

Publications associées (27)

Multi-Region Network Perimeter Control via Model Free Adaptive Iterative Learning Control

Nikolaos Geroliminis, Isik Ilber Sirmatel, Ye Ren

Most perimeter control methods in literature are the model-based schemes. However, accurate modeling of the traffic flow system is hard and time-consuming. On the other hand, macroscopic traffic flow patterns show heavily similarity between days, and data ...

2020

Data driven model free adaptive iterative learning perimeter control for large-scale urban road networks

Nikolaos Geroliminis, Isik Ilber Sirmatel, Ye Ren

Most perimeter control methods in literature are the model-based schemes designing the controller based on the available accurate macroscopic fundamental diagram (MFD) function with well known techniques of modern control methods. However, accurate modelin ...

2020

Materials Cloud, a platform for open computational science

Sebastiaan Philippe Huber, Nicola Marzari, Fernando Gargiulo, Giovanni Pizzi, Aliaksandr Yakutovich, Berend Smit, Martin Uhrin, Snehal Pramod Kumbhar, Spyros Zoupanos, Christoph Leopold Talirz, Elsa Passaro, Casper Welzel Andersen, Daniele Passerone

Materials Cloud is a platform designed to enable open and seamless sharing of resources for computational science, driven by applications in materials modelling. It hosts (1) archival and dissemination services for raw and curated data, together with their ...

2020

Real-Time Processing and Quality Improvement of Synchrophasor Data

Mario Paolone

This paper proposes a real-time algorithm for processing and quality improvement of synchrophasor data (SD). The proposed algorithm first recovers the missing SD reported by phasor measurement units (PMUs), and performs low-rank approximation on data strea ...

2020

A semantic-driven approach toward Industry 4.0

Sangje Cho

The current manufacturing trend is towards sustainability. Due to the degradation of natural resources and the accumulation of waste with an increase in the world population and in the consumption of goods, many countries attempt to switch from a linear to ...

EPFL2020

Sparse and Parametric Modeling with Applications to Acoustics and Audio

Helena Peic Tukuljac

Recent advances in signal processing, machine learning and deep learning with sparse intrinsic structure of data have paved the path for solving inverse problems in acoustics and audio. The main task of this thesis was to bridge the gap between the powerfu ...

EPFL2020

Oblivious Sketching of High-Degree Polynomial Kernels

Mikhail Kapralov, Amir Zandieh

Kernel methods are fundamental tools in machine learning that allow detection of non-linear dependencies between data without explicitly constructing feature vectors in high dimensional spaces. A major disadvantage of kernel methods is their poor scalabili ...

ASSOC COMPUTING MACHINERY2020