Publication

Software Verification by Combining Program Analyses of Adjustable Precision

Related publications (29)

Scaling Language Features for Program Verification

Formal verification of real-world software systems remains challenging for a number of reasons, including lack of automation, friction in specifying properties, and limited support for the diverse programming paradigms used in industry. In this thesis we m ...

EPFL2022

Preprocessing Antarctic Weather Station (AWS) data in python

Michael Lehning, Franziska Gerber

There are many sources providing atmospheric weather station data for the Antarctic continent. However, variable naming, timestamps and data types are highly variable between the different sources. The published python code intends to make processing of di ...

Zenodo2022

Sketches, metrics and fast algorithms

Navid Nouri

As it has become easier and cheaper to collect big datasets in the last few decades, designing efficient and low-cost algorithms for these datasets has attracted unprecedented attention. However, in most applications, even storing datasets as acquired has ...

EPFL2022

Covariance Estimation for Random Surfaces beyond Separability

Tomas Masák

This thesis focuses on non-parametric covariance estimation for random surfaces, i.e.~functional data on a two-dimensional domain. Non-parametric covariance estimation lies at the heart of functional data analysis, and considerations of statistical and com ...

EPFL2022

Simple automation of SEM-EDS spectral maps analysis with Python and the edxia framework

Karen Scrivener, Fabien Jacques Michel Georget, William Wilson

In a recent article, we described the edxia framework, a user-friendly framework to analyse the microstructure of cementitious materials using SEM-EDS hypermaps. The manual approach presented was shown to be efficient to answer the relevant scientific ques ...

WILEY2022

In vivo magnetic resonance P-31-Spectral Analysis With Neural Networks: 31P-SPAWNN

François Lazeyras, Sébastien Courvoisier, Lijing Xin, Julien Songeon

Purpose: We have introduced an artificial intelligence framework, 31P-SPAWNN, in order to fully analyze phosphorus-31 (P-31) magnetic resonance spectra. The flexibility and speed of the technique rival traditional least-square fitting methods, with the per ...

WILEY2022

Synthetic Disinformation Attacks on Automated Fact Verification Systems

Antoine Bosselut

Automated fact-checking is a needed technology to curtail the spread of online misinformation. One current framework for such solutions proposes to verify claims by retrieving supporting or refuting evidence from related textual sources. However, the reali ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2022

CovNet: Covariance networks for functional data on multidimensional domains

Victor Panaretos, Soham Sarkar

Covariance estimation is ubiquitous in functional data analysis. Yet, the case of functional observations over multidimensional domains introduces computational and statistical challenges, rendering the standard methods effectively inapplicable. To address ...

WILEY2022

Low-Power Artificial Neural Network Perceptron Based on Monolayer MoS2

Andras Kis, Aleksandra Radenovic, Zhenyu Wang, Guilherme Migliato Marega, Mukesh Kumar Tripathi

Machine learning and signal processing on the edge are poised to influence our everyday lives with devices that will learn and infer from data generated by smart sensors and other devices for the Internet of Things. The next leap toward ubiquitous electron ...

2022