Publications related to Mixture model

Robustness, replicability and scalability in topic modelling

Approaches for estimating the similarity between individual publications are an area of long -standing interest in the scientometrics and informetrics communities. Traditional techniques have generally relied on references and other metadata, while text mi ...

ELSEVIER2022

Model-Based Clustering of Trends and Cycles of Nitrate Concentrations in Rivers Across France

Camille Roland Marie Minaudo

Elevated nitrate from human activity causes ecosystem and economic harm globally. The factors that control the spatiotemporal dynamics of riverine nitrate concentration remain difficult to describe and predict. We analyzed nitrate concentration from 4450 s ...

SPRINGER2022

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

A mixture model to take into account diluted gas in liquid flow: applications to aluminium electrolysis

Emile Tryphon Pierre Soutter

Aluminium is a metal sought in the industry because of its various physical properties. It is produced by an electrolysis reduction process in large cells. In these cells, a large electric current goes through the electrolytic bath and the liquid aluminium ...

EPFL2022

Hidden Markov Modeling Over Graphs

Ali H. Sayed, Mert Kayaalp, Stefan Vlaski, Virginia Bordignon

This work proposes a multi-agent filtering algorithm over graphs for finite-state hidden Markov models (HMMs), which can be used for sequential state estimation or for tracking opinion formation over dynamic social networks. We show that the difference fro ...

IEEE2022

Technology Strategy in Dynamic Environments: A Computational Analysis of the Automation of Routines, the Organization of AI, and the Evaluation of Technology Risk

Maximilian Wieland Hofer

In this dissertation, I develop theory and evidence to argue that new technologies are central to how firms organize to create and capture value. I use computational methods such as reinforcement learning and probabilistic topic modeling to investigate thr ...

EPFL2022

Information-driven transitions in projections of underdamped dynamics

Daniel Maria Busiello, Giorgio Nicoletti, Amos Maritan

Low-dimensional representations of underdamped systems often provide useful insights and analytical tractability. Here, we build such representations via information projections, obtaining an optimal model that captures the most information on observed spa ...

AMER PHYSICAL SOC2022

From Generalisation Error to Transportation-cost Inequalities and Back

Michael Christoph Gastpar, Amedeo Roberto Esposito

In this work, we connect the problem of bounding the expected generalisation error with transportation-cost inequalities. Exposing the underlying pattern behind both approaches we are able to generalise them and go beyond Kullback- Leibler Divergences/Mutu ...

2022

HybridSDF: Combining Deep Implicit Shapes and Geometric Primitives for 3D Shape Representation and Manipulation

Pascal Fua, Nicolas Talabot, Subeesh Vasu, Artem Lukoianov

Deep implicit surfaces excel at modeling generic shapes but do not always capture the regularities present in manufactured objects, which is something simple geometric primitives are particularly good at. In this paper, we propose a representation combinin ...

2022

Multiple testing with test statistics following heavy-tailed distributions

Zhiwen Jiang

In multiple testing problems where the components come from a mixture model of noise and true effect, we seek to first test for the existence of the non-zero components, and then identify the true alternatives under a fixed significance level

\alpha

. Two ...

EPFL2021

Mixture model

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Robustness, replicability and scalability in topic modelling

Model-Based Clustering of Trends and Cycles of Nitrate Concentrations in Rivers Across France

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

A mixture model to take into account diluted gas in liquid flow: applications to aluminium electrolysis

Hidden Markov Modeling Over Graphs

Technology Strategy in Dynamic Environments: A Computational Analysis of the Automation of Routines, the Organization of AI, and the Evaluation of Technology Risk

Information-driven transitions in projections of underdamped dynamics

From Generalisation Error to Transportation-cost Inequalities and Back

HybridSDF: Combining Deep Implicit Shapes and Geometric Primitives for 3D Shape Representation and Manipulation

Multiple testing with test statistics following heavy-tailed distributions

Robustness, replicability and scalability in topic modelling

Hidden Markov Modeling Over Graphs

From Generalisation Error to Transportation-cost Inequalities and Back

HybridSDF: Combining Deep Implicit Shapes and Geometric Primitives for 3D Shape Representation and Manipulation

Technology Strategy in Dynamic Environments: A Computational Analysis of the Automation of Routines, the Organization of AI, and the Evaluation of Technology Risk

Multiple testing with test statistics following heavy-tailed distributions

Model-Based Clustering of Trends and Cycles of Nitrate Concentrations in Rivers Across France

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

A mixture model to take into account diluted gas in liquid flow: applications to aluminium electrolysis

Information-driven transitions in projections of underdamped dynamics