Publications related to Latent variable model

Robust machine learning for neuroscientific inference

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024

An Ordinal Latent Variable Model of Conflict Intensity

Robert West

Measuring the intensity of events is crucial for monitoring and tracking armed conflict. Advances in automated event extraction have yielded massive data sets of '' who did what to whom '' micro-records that enable datadriven approaches to monitoring confl ...

Assoc Computational Linguistics-Acl2023

Personalizable intervention systems to promote healthy behavior change

Igor Kulev

Adopting healthy behaviors can prevent the onset of many adverse health conditions. However, behavior changes are difficult to make, and often, people who like to improve their behaviors do not know how to do that. Personalizable intervention systems could ...

EPFL2020

Learning Linear Non-Gaussian Causal Models in the Presence of Latent Variables

Negar Kiyavash, Saber Salehkaleybar, Kun Zhang

We consider the problem of learning causal models from observational data generated by linear non-Gaussian acyclic causal models with latent variables. Without considering the effect of latent variables, the inferred causal relationships among the observed ...

Microtome Publishing2020

The Tonal Diffusion Model

Martin Alois Rohrmeier, Fabian Claude Moss, Robert Lieck

Pitch-class distributions are of central relevance in music information retrieval, computational musicology and various other fields, such as music perception and cognition. However, despite their structure being closely related to the cognitively and musi ...

2020

Collaborative Recurrent Neural Networks for Dynamic Recommender Systems

Matthias Grossglauser, Lucas Maystre, Young Jun Ko

Modern technologies enable us to record sequences of online user activity at an unprecedented scale. Although such activity logs are abundantly available, most approaches to recommender systems are based on the rating-prediction paradigm, ignoring temporal ...

2016

Correcting for endogeneity due to omitted attitudes: Empirical assessment of a modified MIS method using RP mode choice data

Michel Bierlaire, Matthieu Marie Cochon de Lapparent, Anna Fernández Antolín

In this paper we extend the Multiple Indicator Solution (MIS) so that it can also be used to account for endogeneity when there are interactions between observed and unobserved factors in the specification of the utility function. We develop the theoretica ...

Elsevier Sci Ltd2016

Model selection for partial least squares calibration and implications for analysis of atmospheric organic aerosol samples with mid-infrared spectroscopy

Satoshi Takahama

In developing partial least squares calibration models, selecting the number of latent variables used for their construction to minimize both model bias and model variance remains a challenge. Several metrics exist for incorporating these trade-offs, but t ...

Wiley-Blackwell2015

Laplacian Matrix Learning for Smooth Graph Signal Representation

Pascal Frossard, Pierre Vandergheynst, Ntorina Thanou, Xiaowen Dong

The construction of a meaningful graph plays a crucial role in the emerging field of signal processing on graphs. In this paper, we address the problem of learning graph Laplacians, which is similar to learning graph topologies, such that the input data fo ...

2015

Measuring the Effects of Economic Crisis on Users' Perceptions of Public Transport Quality

Dimitrios Efthymiou

Research was conducted to measure the effects of the economic crisis on public transport quality, user satisfaction, and transit demand. The survey used in this research extended a research effort that began in 2008; the survey aimed to analyze the variabi ...

National Academy of Sciences2014

Integrating psychometric indicators in latent class choice models

Michel Bierlaire, Ricardo Daniel Hurtubia González, Aurélie Glerum, My Hang Nguyen

Latent class models are a convenient and intuitive way to introduce taste heterogeneity in discrete choice models by relating attributes of the decision makers with unobserved behavioral classes, hence allowing for a more accurate market segmentation. Esti ...

Pergamon-Elsevier Science Ltd2014

Using semi-open questions to integrate perceptions in choice models

Michel Bierlaire, Aurélie Glerum, Bilge Atasoy

This research investigates the measurement of perceptions by means of adjectives freely reported by respondents in semi-open questions. It involved the use of semi-open responses of 1'763 Swiss individuals to develop indicators for a latent variable repres ...

Elsevier Sci Ltd2014

Estimation of bid functions for location choice and price modeling with a latent variable approach

Michel Bierlaire, Ricardo Daniel Hurtubia González

A new approach for the estimation of bid-rent functions for residential location choice is proposed. The method is based on the bid-auction approach and considers that the expected maximum bid of the auction is a latent variable that can be related to obse ...

Springer2014

Attitudes towards mode choice in Switzerland

Michel Bierlaire, Aurélie Glerum, Bilge Atasoy

We integrate latent attitudes of individuals into a mode choice model through latent variable and latent class models with the help of psychometric indicators that enable us to measure these attitudes. The aim of the inclusion of attitudes is to better und ...

2013

A Sequential Topic Model for Mining Recurrent Activities from Long Term Video Logs

Jean-Marc Odobez, Jagannadan Varadarajan, Rémi Emonet

This paper introduces a novel probabilistic activity modeling approach that mines recurrent sequential patterns called motifs from documents given as word×time count matrices (e.g., videos). In this model, documents are represented as a mixture of sequenti ...

Springer2013

Linking response quality to survey engagement: A combined random scale and latent variable approach

Amanda Blomberg Stathopoulos

Recent interest in the topic of random scale heterogeneity in discrete choice data has led to the development of specialised tools such as the G-MNL model, as well as repeated claims that studies which fail to separate scale heterogeneity from heterogeneit ...

2013

Its not that I dont care, I just dont care very much: confounding between attribute non-attendance and taste heterogeneity

Amanda Blomberg Stathopoulos

With the growing interest in the topic of attribute non-attendance, there is now widespread use of latent class (LC) structures aimed at capturing such behaviour, across a number of different fields. Specifically, these studies rely on a confirmatory LC mo ...

Springer2013

Statistical Modeling of Spatial Extremes

Anthony Christopher Davison, Simone Padoan

The areal modeling of the extremes of a natural process such as rainfall or temperature is important in environmental statistics; for example, understanding extreme areal rainfall is crucial in flood protection. This article reviews recent progress in the ...

Institute of Mathematical Statistics2012