Publications related to Noncentral t-distribution

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire, Thomas Gasos, Prateek Bansal

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

2023

Networks of Ethereum Non-Fungible Tokens: A graph-based analysis of the ERC-721 ecosystem

Marco Mattavelli, Simone Casale Brunet

Non-fungible tokens (NFTs) as a decentralized proof of ownership represent one of the main reasons why Ethereum is a disruptive technology. This paper presents the first systematic study of the interactions occurring in a number of NFT ecosystems. We illus ...

IEEE2021

Comparison of non-parametric T2 relaxometry methods for myelin water quantification

Jean-Philippe Thiran, Tobias Kober, Tom Hilbert, Erick Jorge Canales Rodriguez, Gian Franco Piredda, Marco Pizzolato, Thomas Yu, Alessandro Daducci, Nicolas Kunz

Multi-component T2 relaxometry allows probing tissue microstructure by assessing compartment-specific T2 relaxation times and water fractions, including the myelin water fraction. Non-negative least squares (NNLS) with zero-order Tikhonov regularization is ...

2021

Test of lepton flavor universality and search for lepton flavor violation in B -> Kll decays

Olivier Schneider, Yiming Li, Mingkui Wang, Chao Wang, Sun Hee Kim, Donghyun Kim, Xiao Wang, Lei Li

We present measurements of the branching fractions for the decays B -> K mu(+)mu(-) and B -> Ke(+)e(-), and their ratio (R-K), using a data sample of 711 fb(-1) that contains 772 x 10(6) B (B) over bar events. The data were collected at the Gamma(4S) reson ...

Springer Nature2021

A t-distribution based operator for enhancing out of distribution robustness of neural network classifiers

Philip Neil Garner

Neural Network (NN) classifiers can assign extreme probabilities to samples that have not appeared during training (out-of-distribution samples) resulting in erroneous and unreliable predictions. One of the causes for this unwanted behaviour lies in the us ...

IEEE Institute of Electrical and Electronics Engineers2020

Design and Decoding of Irregular LDPC Codes Based on Discrete Message Passing

Andreas Peter Burg

We consider discrete message passing (MP) decoding of low-density parity check (LDPC) codes based on information-optimal symmetric look-up table (LUT). A link between discrete message labels and the associated log-likelihood ratio values (defined in terms ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Reconstruction Methods for Cryo-Electron Microscopy: From Model-based to Data-driven

Laurène Donati

The topic of this thesis is the development of new reconstruction methods for cryo-electron microscopy (cryo-EM). Cryo-EM has revolutionized the field of structural biology over the last decade and now permits the regular discovery of biostructures. Yet, t ...

EPFL2020

Approximate Decoding for Network Coded Inter-dependent Data

Pascal Frossard, Nikolaos Thomos, Hyung Gon Park

In this paper, we consider decoding of loss tolerant data encoded by network coding and transmitted over error-prone networks. Intermediate network nodes typically perform the random linear network coding in a Galois field and a Gaussian elimination is use ...

Elsevier Science Bv2016

An efficient initialization mechanism of neurons for Winner Takes All Neural Network implemented in the CMOS technology

Pierre-André Farine, Rafal Tomasz Dlugosz

The paper presents a new initialization mechanism based on a Convex Combination Method (CCM) for Kohonen self-organizing Neural Networks (NNs) realized in the CMOS technology. A proper selection of initial values of the neuron weights exhibits a strong imp ...

Elsevier Science Inc2015

On the Convergence Speed of Spatially Coupled LDPC Ensembles

Vahid Aref

Spatially coupled low-density parity-check codes show an outstanding performance under the low-complexity belief propagation (BP) decoding algorithm. They exhibit a peculiar convergence phenomenon above the BP threshold of the underlying non-coupled ensemb ...

2013

Impact of stochastic fluctuations in storage-discharge relations on streamflow distributions

Andrea Rinaldo, Enrico Bertuzzo, Samir Suweis, Gianluca Botter

In this paper we extend recent theoretical results on the structure of the probability density function of streamflows forced by stochastic rainfall sequences. Our extension is aimed at incorporating an additional, independent source of variability assumed ...

2010

Uncovering the topology of configuration space networks

Paolo De Los Rios, David Sébastien Morton de Lachapelle, David Gfeller

The configuration space network (CSN) of a dynamical system is an effective approach to represent the ensemble of configurations sampled during a simulation and their dynamic connectivity. To elucidate the connection between the CSN topology and the underl ...

2007

New model for rigorous analysis of LT-codes

Mohammad Amin Shokrollahi

We present a new model for LT codes which simplifies the analysis of the error probability of decoding by belief propagation. For any given degree distribution, we provide the first rigorous expression for the limiting bit-error probability as the length o ...

2006

A statistical physics perspective of complex networks : from the architecture of the Internet and the brain to the spreading of an epidemic

Thomas Petermann

A statistical physics perspective of complex networks: from the architecture of the Internet and the brain to the spreading of an epidemic Statistical physics has revealed itself as the ideal framework to describe large networks appearing in a variety of d ...

EPFL2005