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Publications associées (22)

turboMagnon - A code for the simulation of spin-wave spectra using the Liouville-Lanczos approach to time-dependent density-functional perturbation theory

Iurii Timrov

We introduce turboMagnon, an implementation of the Liouville-Lanczos approach to linearized time-dependent density-functional theory, designed to simulate spin-wave spectra in solid-state materials. The code is based on the noncollinear spin-polarized fram ...

ELSEVIER2022

Templates for 3D Object Pose Estimation Revisited: Generalization to New Objects and Robustness to Occlusions

Mathieu Salzmann, Vincent Lepetit, Yinlin Hu

We present a method that can recognize new objects and estimate their 3D pose in RGB images even under partial occlusions. Our method requires neither a training phase on these objects nor real images depicting them, only their CAD models. It relies on a s ...

IEEE COMPUTER SOC2022

U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture Search

Pascal Frossard, Ahmet Caner Yüzügüler, Nikolaos Dimitriadis

Optimizing resource utilization in target platforms is key to achieving high performance during DNN inference. While optimizations have been proposed for inference latency, memory footprint, and energy consumption, prior hardware-aware neural architecture ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

HP - A code for the calculation of Hubbard parameters using density-functional perturbation theory

Nicola Marzari, Iurii Timrov, Matteo Cococcioni

We introduce HP, an implementation of density-functional perturbation theory, designed to compute Hubbard parameters (on-site U and inter-site V ) in the framework of DFT+U and DFT+U+V. The code does not require the use of computationally expensive superce ...

ELSEVIER2022

Automated Verification of Network Function Binaries

George Candea, Aikaterini Argyraki, Solal Vincenzo Pirelli

Formally verifying the correctness of software network functions (NFs) is necessary for network reliability, yet existing techniques require full source code and mandate the use of specific data structures. We describe an automated technique to verify NF b ...

USENIX Association2022

Virtual reality enabled building-data management through the combination of a fully integrated IFC-BIM model and an IoT-based building management system

Sergi Aguacil Moreno, Laurent Deschamps, Sebastian Duque Mahecha, Alexandre Denis Stoll, Tiago De Sousa Pereira

Professionals involved in building construction and monitoring increasingly implement new practices made available by Building Information Modelling (BIM), Virtual Reality (VR) and the Internet of Things (IoT). In spite of numerous efforts, most methods in ...

2021

A Study on More Realistic Room Simulation for Far-Field Keyword Spotting

Robin Scheibler, Eric Bezzam

We investigate the impact of more realistic room simulation for training far-field keyword spotting systems without fine-tuning on in-domain data. To this end, we study the impact of incorporating the following factors in the room impulse response (RIR) ge ...

IEEE2020

Current-Based Data-Retention-Time Characterization of Gain-Cell Embedded DRAMs Across the Design and Variations Space

Andreas Peter Burg, Adam Shmuel Teman, Robert Giterman, Andrea Bonetti

The rise of data-intensive applications has resulted in an increasing demand for high-density and low-power on-chip embedded memories. Gain-cell embedded DRAM (GC-eDRAM) is a logic-compatible alternative to conventional static random access memory (SRAM) w ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Safe Initialization of Objects

Martin Odersky, Fengyun Liu, Paolo Giosuè Giarrusso, Angelos Bimpoudis

Every newly created object goes through several initialization states: starting from a state where all fields are uninitialized until all of them are assigned. Any operation on the object during its initialization process, which usually happens in the cons ...

2020

A Type-and-Effect System for Object Initialization

Martin Odersky, Fengyun Liu, Paolo Giosuè Giarrusso, Angelos Bimpoudis

ASSOC COMPUTING MACHINERY2020

Using an antenna as a tool for studying microturbulence and zonal structures in tokamaks with a global gyrokinetic GPU-enabled particle-in-cell code

Noé Thomas Elie Ohana

In order to get a better understanding of the interaction of plasma microinstabilities and associated turbulence with specific modes, an antenna is implemented in the global gyrokinetic Particle-In-Cell (PIC) code ORB5. It consists in applying an external ...

EPFL2020

The Sixth Visual Object Tracking VOT2018 Challenge Results

Wei Wu, Qiang Wang, Bo Li, Yunpeng Li, Feng Li, Erhan Gündogdu

The Visual Object Tracking challenge VOT2018 is the sixth annual tracker benchmarking activity organized by the VOT initiative. Results of over eighty trackers are presented; many are state-of-the-art trackers published at major computer vision conferences ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

Streaming From a Moving Platform with Real-Time and Playback Distortion Constraints

Laura Toni, Giuseppe Cocco

Video streaming from remotely controlled moving platforms such as drones have stringent constraints in terms of delay. In some applications such videos have to provide real-time visual feedback to the pilot with an acceptable distortion while satisfying hi ...

IEEE2019

Data-Retention-Time Characterization of Gain-Cell eDRAMs across the Design and Variations Space

Andreas Peter Burg, Andrea Bonetti

The rise of data-intensive applications has increased the demand for high-density and low-power embedded memories. Among them, the gain-cell embedded DRAM (GC-eDRAM) is a suitable alternative to the static random access memory (SRAM) due to its high memory ...

IEEE2019

PyLandStats: An open-source Pythonic library to compute landscape metrics

Martí Bosch Padrós

Quantifying the spatial pattern of landscapes has become a common task of many studies in landscape ecology. Most of the existing software to compute landscape metrics is not well suited to be used in interactive environments such as Jupyter notebooks nor ...

2019

Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence Images

Matthieu Jean-Michel Philippe Broisin

Identifying nuclei is often a critical first step in analyzing microscopy images of cells and classical image processing algorithms are most commonly used for this task. Recent developments in deep learning can yield superior accuracy, but typical evaluati ...

2019

Acoustic DoA Estimation by One Unsophisticated Sensor

Martin Vetterli, Ivan Dokmanic, Dalia Salem Hassan Fahmy El Badawy

We show how introducing known scattering can be used in direction of arrival estimation by a single sensor. We first present an analysis of the geometry of the underlying measurement space and show how it enables localizing white sources. Then, we extend t ...

Springer Verlag2017

StreamFlow 1.0: an extension to the spatially distributed snow model Alpine3D for hydrological modelling and deterministic stream temperature prediction

Michael Lehning, Wolf Hendrik Huwald, Francesco Comola, Aurélien Gallice, Tristan Jonas Brauchli

Climate change is expected to strongly impact the hydrological and thermal regimes of Alpine rivers within the coming decades. In this context, the development of hydrological models accounting for the specific dynamics of Alpine catchments appears as one ...

Copernicus Gesellschaft Mbh2016

Modern techniques and applications for real-time non-rigid registration

Mark Pauly, Hao Li, Sofien Bouaziz, Andrea Tagliasacchi

Registration algorithms are an essential component of many computer graphics and computer vision systems. With recent technological advances in RGBD sensors (color plus depth), an active area of research is in techniques combining color, geometry, and lear ...

2016

Measuring and Managing Switch Diversity in Software Defined Networks

Maciej Leszek Kuzniar

Software Defined Networking (SDN) is a novel approach to building computer networks. Improved flexibility, simplified management and cost reduction promised by SDN makes many see it as the future of networking. The main insight of SDN is the separation of ...

EPFL2016