Concept

Metrizable topological vector space

Publications associées (20)

Universal Architectures for the Learning of Polyhedral Norms and Convex Regularizers

This paper addresses the task of learning convex regularizers to guide the reconstruction of images from limited data. By imposing that the reconstruction be amplitude-equivariant, we narrow down the class of admissible functionals to those that can be expressed as a power of a seminorm. We then show that such functionals can be approximated to arbitrary precision with the help of polyhedral norms. In particular, we identify two dual parameterizations of such systems: (i) a synthesis (or atomic) form with a

Society for Industrial and Applied Mathematics2026

Instantaneous Complex Phase and Frequency: Conceptual Clarification and Equivalence between Formulations

This letter seeks to clarify the different existing definitions of both instantaneous complex phase and frequency as well as their equivalence under standard modeling assumptions considered for transmission systems, i.e. balanced positive sequence operation, sole presence of electro-mechanical transient dynamics and absence of harmonics and interharmonics. To achieve this, the two fundamental definitions, i.e., those based on either the use of (i) analytic signals or (ii) space vectors, together with the pr

IEEE Institute of Electrical and Electronics Engineers2026

Explainable zero-shot transfer learning for cross-domain In-Situ acoustic monitoring in laser powder bed fusion process using learnable wavelet scattering

• Learnable Wavelet Scattering network decodes acoustic fingerprints of melt-pool dynamics from data, bridging physics and learning. • Adaptive Morlet wavelets converge toward stable sub-40 kHz bands that capture the temporal dynamics of melt-pool regime transitions. • The causal framework spectrally localizes keyhole-mode activity, confining its acoustic signature to low-frequency bands below 30 kHz. • The framework achieves ∼97–99% accuracy and retains robust performance across drift domain embeddings wit

Elsevier BV2026

Using large language models to understand the public discourse towards vaccination in Brazil between January 2013 and December 2019

Summary Background Vaccination against infectious diseases prevents diseases, saves lives, and reduces healthcare costs. However, trust, accessibility, and public perceptions influence vaccine acceptance or refusal. Risk communication and community engagement (RCCE) is key in addressing inaccurate claims and misconceptions, and improving vaccine coverage. This study examines how public stance towards vaccination evolved in Brazil from 2013 to 2019 using Twitter data. Methods We collected tweets in Portugues

bioRxiv2025

TopoTome: Topology-informed unsupervised segmentation and analysis of 3D images

Biological systems are three-dimensional and complex. Today, images of biological structures can be acquired using different imaging technologies and at increasing resolutions. However, identifying relevant structural features in three-dimensional (3D) images remains a significant challenge. 3D image segmentation is usually performed using deep-learning segmentation models. Such models are trained on manually annotated and segmented, dataset-specific images. Consequently, they rarely generalize across datas

bioRxiv2025

A Topological Approach to Magnetic Nulls

Magnetic nulls are locations where the magnetic field vanishes. They determine to a large degree the magnetic connectivity in a system, and are sites of magnetic reconnection. We describe a novel approach to understanding movement, appearance, and disappearance of nulls in magnetic fields. This approach is based on the concept of isotropes, or lines where the field direction is constant. These lines are streamlines of a vector field whose flux is sourced by the topological indices of nulls, and can be conce

IOP Publishing Ltd2025

Motivic classes of Hilbert schemes and invariants of unibranch curve singularities via motivic integration

In this thesis, we study motivic classes of punctual Hilbert schemes and their relationship to Igusa zeta functions and motivic integration. We start with the case of varieties in a smooth ambient variety, for which we provide an equality between the generating series of motivic classes of curvilinear punctual Hilbert schemes with a particular Igusa zeta function, that we refer to as the curvilinear Igusa zeta function. Studying the behavior of arcs under embedded resolutions, we can express the curviline

EPFL2025

Unsupervised Learning of Representations for Lexical Entailment Detection

Detecting lexical entailment plays a fundamental role in a variety of natural language processing tasks and is key to language understanding. Unsupervised methods still play an important role due to the lack of coverage of lexical databases in some domains and languages. Most of the previous approaches were either based on statistical hypothesis of specific entailment relations or tried to encode word relations in low-dimensional vector embeddings. This thesis builds upon one of the few approaches which int

2018

Differential geometry applied to crystallography

The mathematical facet of modern crystallography is essentially based on analytical geometry, linear algebra as well as group theory. This study endeavours to approach the geometry and symmetry of crystals using the tools furnished by differential geometry ...

EPFL2009

Stability and Delay Bounds in Heterogeneous Networks of Aggregate Schedulers

Jean-Yves Le Boudec

Aggregate scheduling is one of the most promising solutions to the issue of scalability in networks, like DiffServ networks and high speed switches, where hard QoS guarantees are required. For networks of FIFO aggregate schedulers, the main existing sufficient conditions for stability (the possibility to derive bounds to delay and backlog at each node) are of little practical utility, as they are either relative to specific topologies, or based on strong ATM- like assumptions on the network (the so-called ”

2007

Revisiting Doddington's Zoo: A Systematic Method to Assess User-dependent Variabilities

A systematic analysis of user-dependent performance variability in the context of automatic speaker verification was first studied by Doddington \etal (1998). Different categories of users were distinguished and were called by animal names such as sheep, goats, lambs and wolves. Although such distinctions are important, it does not directly discriminate well-behaved'' users from badly behaved'' users. In our context, the badly behaved users are those who will bring the performance down when added to the

IDIAP2006

Revisiting Doddington's Zoo: A Systematic Method to Assess User-dependent Variabilities

2006

Discriminative Kernel-Based Phoneme Sequence Recognition

We describe a new method for phoneme sequence recognition given a speech utterance. In contrast to HMM-based approaches, our method uses a kernel-based discriminative training procedure in which the learning process is tailored to the goal of minimizing the Levenshtein distance between the predicted phoneme sequence and the correct sequence. The phoneme sequence predictor is devised by mapping the speech utterance along with a proposed phoneme sequence to a vector-space endowed with an inner-product that is

IDIAP2006

Discriminative Kernel-Based Phoneme Sequence Recognition

We describe a new method for phoneme sequence recognition given a speech utterance, which is not based on the HMM. In contrast to HMM-based approaches, our method uses a discriminative kernel-based training procedure in which the learning process is tailored to the goal of minimizing the Levenshtein distance between the predicted phoneme sequence and the correct sequence. The phoneme sequence predictor is devised by mapping the speech utterance along with a proposed phoneme sequence to a vector-space endowe

2006

F-ratio Client-Dependent Normalisation on Biometric Authentication Tasks

This study investigates a new client-dependent normalisation to improve biometric authentication systems. There exists many client-de-pendent score normalisation techniques applied to speaker authentication, such as Z-Norm, D-Norm and T-Norm. Such normalisation is intended to adjust the variation across different client models. We propose ``F-ratio'' normalisation, or F-Norm, applied to face and speaker authentication systems. This normalisation requires only that as few as two client-dependent accesses are

2005

An Investigation of F-ratio Client-Dependent Normalisation on Biometric Authentication Tasks

This study investigates a new \emph{client-dependent normalisation} to improve biometric authentication systems. There exists many client-de-pendent score normalisation techniques applied to speaker authentication, such as Z-Norm, D-Norm and T-Norm. Such normalisation is intended to adjust the variation across different client models. We propose ``F-ratio'' normalisation, or F-Norm, applied to face and speaker authentication systems. This normalisation requires only that \emph{as few as} two client-dependen

IDIAP2004

Improving Single Modal and Multimodal Biometric Authentication Using F-ratio Client-Dependent Normalisation

This study investigates a new client-dependent normalisation to improve a single biometric authentication system, as well as its effects on fusion. There exists two families of client-dependent normalisation techniques, often applied to speaker authentication. They are client-dependent score and threshold normalisation techniques. Examples of the former family of techniques are Z-Norm, D-Norm and T-Norm. There is also a vast amount of literature on the latter family of techniques. Both families are surveyed

IDIAP2004

Proxys Internet avancés

Philippe Daniel Rochat

Since the 90's, the Internet has tremendously evolved in terms of number and diversity of available services. In this trend, proxies are playing a central role and are spread all over the net. Today, the only functionality of proxies is to speed content access through caching only considering statistics based on use made by a user group, all together. Nowadays, evolutions are focusing on two main trends: specific infrastructures that do not comply anymore with the Web universality or individual applications

EPFL2003

A history of rational homotopy theory

Kathryn Hess Bellwald

Rational homotopy theory is the study of topological spaces “modulo torsion”. When rational homotopy theorists calculate algebraic invariants of a topological space, such as its homotopy or homology groups, they retain only the nontorsion information. Algebraic models of topological spaces are the most important tools of the rational homotopy theorist.

Elsevier Science B.V.1999

Ethyl acetate

Albert Renken

AcOEt was prepd. continuously by the addn. of C2H4 to AcOH in a process wherein C2H4 and AcOH were alternately passed into a reactor where they were contacted at 138-47 Deg with a SiO2 catalyst impregnated with H2SO4 or Et2SO4. The surface area of the SiO2 was crit.; e.g., at 120 m2/g the wt.% of C2H4, was 60.0, but at 110 and 160 m2/g the wt.% AcOEt was only 34.2 and 37.4, resp. Selectivity was .apprx.100%. [on SciFinder (R)]

(Hoechst A.-G., Fed. Rep. Ger.).1977

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Publications associées (20)

Universal Architectures for the Learning of Polyhedral Norms and Convex Regularizers

Michaël Unser

Society for Industrial and Applied Mathematics2026

Instantaneous Complex Phase and Frequency: Conceptual Clarification and Equivalence between Formulations

IEEE Institute of Electrical and Electronics Engineers2026

Explainable zero-shot transfer learning for cross-domain In-Situ acoustic monitoring in laser powder bed fusion process using learnable wavelet scattering

Elsevier BV2026

Using large language models to understand the public discourse towards vaccination in Brazil between January 2013 and December 2019

bioRxiv2025