Publications related to Information-driven transitions in projections of underdamped dynamics

Spectral Estimators for High-Dimensional Matrix Inference

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

Jan Sickmann Hesthaven, Federico Pichi

The present work proposes a framework for nonlinear model order reduction based on a Graph Convolutional Autoencoder (GCA-ROM). In the reduced order modeling (ROM) context, one is interested in obtaining real -time and many-query evaluations of parametric ...

Academic Press Inc Elsevier Science2024

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Sachin Basil John

In the current era of big data, aggregation queries on high-dimensional datasets are frequently utilized to uncover hidden patterns, trends, and correlations critical for effective business decision-making. Data cubes facilitate such queries by employing p ...

EPFL2023

Analysis of the influence of errors in DNA-based image coding

Touradj Ebrahimi, Davi Nachtigall Lazzarotto, Michela Testolina

In the last decade, DNA has been increasingly investigated as an alternative medium for cold data storage, presenting several advantages over standard hard drives such as a higher density, longer lifespan and lower energy consumption. However, such coding ...

2023

Sparse Autoencoders for Speech Modeling and Recognition

Selen Hande Kabil

Speech recognition-based applications upon the advancements in artificial intelligence play an essential role to transform most aspects of modern life. However, speech recognition in real-life conditions (e.g., in the presence of overlapping speech, varyin ...

EPFL2023

Damping of flexure blades based on bi-material additive manufacturing

Simon Nessim Henein, Florent Cosandier, Nicolas Blondiaux, Elias Sebastian Klauser, Loïc Benoît Tissot-Daguette, Nikola Kalentics, Lisa Salamin, Florent Alexandre Boudoire

Flexure-based mechanisms have become state-of-the-art solutions for the design of high-precision mechanisms, free from friction wear, backlash, and lubrication. These properties which are necessary for applications in ultraclean or harsh environments, neve ...

2023

Perspective Aware Road Obstacle Detection

Pascal Fua, Mathieu Salzmann, Krzysztof Maciej Lis, Sina Honari

While road obstacle detection techniques have become increasingly effective, they typically ignore the fact that, in practice, the apparent size of the obstacles decreases as their distance to the vehicle increases. In this letter, we account for this by c ...

2023

A machine learning approach to portfolio pricing and risk management for high-dimensional problems

Damir Filipovic

We present a general framework for portfolio risk management in discrete time, based on a replicating martingale. This martingale is learned from a finite sample in a supervised setting. Our method learns the features necessary for an effective low-dimensi ...

WILEY2022

HIERARCHICAL MARKOV CHAIN MONTE CARLO METHODS FOR BAYESIAN INVERSE PROBLEMS

Juan Pablo Madrigal Cianci

This thesis is devoted to the construction, analysis, and implementation of two types of hierarchical Markov Chain Monte Carlo (MCMC) methods for the solution of large-scale Bayesian Inverse Problems (BIP). The first hierarchical method we present is base ...

EPFL2022

Multi-scale experimental testing on variable stiffness and damping components for semi-active structural control

Gennaro Senatore

This paper presents experimental testing of a new semi-active vibration control device comprising a shape memory polymer (SMP) core that is reinforced by an SMP-aramid composite skin. This control device works as a load-transfer component that can be integ ...

ELSEVIER SCI LTD2022

A Variational Inference Approach to Learning Multivariate Wold Processes

Patrick Thiran, Matthias Grossglauser, Seyed Jalal Etesami, William Trouleau, Negar Kiyavash

Temporal point-processes are often used for mathematical modeling of sequences of discrete events with asynchronous timestamps. We focus on a class of temporal point-process models called multivariate Wold processes (MWP). These processes are well suited t ...

MICROTOME PUBLISHING2021

Spectral Measurement and Classification in the Era of Big Data

Marilyne Andersen, Forrest Simon Webler

The measurement and classification of light is essential across many scientific disciplines. Devices used to measure light range from the highly precise scanning spectroradiometers to the more practical compact multichannel filter-array type imaging sensor ...

2021

Chemiscope: interactive structure-property explorer for materials and molecules

Michele Ceriotti, Guillaume André Jean Fraux

The number of materials or molecules that can be created by combining different chemical elements in various proportions and spatial arrangements is enormous. Computational chemistry can be used to generate databases containing billions of potential struct ...

2020

Protecting Mobile Food Diaries from Getting too Personal

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

Smartphone applications that use passive sensing to support human health and well-being primarily rely on: (a) generating low-dimensional representations from high-dimensional data streams; (b) making inferences regarding user behavior; and (c) using those ...

Association for Computing Machinery2020

Common Information Components Analysis

Michael Christoph Gastpar, Erixhen Sula

We give an information-theoretic interpretation of Canonical Correlation Analysis (CCA) via (relaxed) Wyner's common information. CCA permits to extract from two high-dimensional data sets low-dimensional descriptions (features) that capture the commonalit ...

IEEE2020

Joint Angular Refinement and Reconstruction for Single-Particle Cryo-EM

Michaël Unser, Laurène Donati, Mona Zehni, Emmanuel Emilien Louis Soubies

Single-particle cryo-electron microscopy (cryo-EM) reconstructs the three-dimensional (3D) structure of bio-molecules from a large set of 2D projection images with random and unknown orientations. A crucial step in the single-particle cryo-EM pipeline is 3 ...

2020

From the Principle of Inertia to the Death Drive: The Influence of the Second Law of Thermodynamics on the Freudian Theory of the Psychical Apparatus

Jean-Philippe Ansermet, Pierre Magistretti

In the Freudian theory of the psychical apparatus, the introduction from the 1920s onward of the second drive dualism appears as a major turning point. The idea of a "death drive," first expressed in Beyond the Pleasure Principle (Freud, 1920), is generall ...

Frontiers Media2020

Graph Laplacian Mixture Model

Pascal Frossard, Hermina Petric Maretic

Graph learning methods have recently been receiving increasing interest as means to infer structure in datasets. Most of the recent approaches focus on different relationships between a graph and data sample distributions, mostly in settings where all avai ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Vibration Suppression Through Variable Stiffness and Damping Structural Joints

Gennaro Senatore

This paper introduces a new semi-active strategy for vibration control of truss and frame structures equipped with variable stiffness and damping joints which consist of a shape memory polymer (SMP) core reinforced by an SMP-aramid composite skin. When the ...

2020

Modifier Adaptation as a Feedback Control Scheme

Dominique Bonvin, Alejandro Gabriel Marchetti, Sean Costello, Tafarel de Avila Ferreira

As a real-time optimization technique, modifier adaptation (MA) has gained much significance in recent years. This is mainly due to the fact that MA can deal explicitly with structural plant-model mismatch and unknown disturbances. MA is an iterative techn ...

AMER CHEMICAL SOC2020