Publications associées à Flexible Statistical Inference for Multivariate Extremes

Publications associées (11)

Interactive symbolic regression with co-design mechanism through offline reinforcement learning

Wenqing Zhou, Olga Fink, Michele Viscione

Symbolic Regression holds great potential for uncovering underlying mathematical and physical relationships from observed data. However, the vast combinatorial space of possible expressions poses significant challenges for previous online search methods an ...

Springer Science and Business Media LLC2025

Drift Estimation of Multiscale Diffusions Based on Filtered Data

Assyr Abdulle, Andrea Zanoni, Giacomo Garegnani

We study the problem of drift estimation for two-scale continuous time series. We set ourselves in the framework of overdamped Langevin equations, for which a single-scale surrogate homogenized equation exists. In this setting, estimating the drift coeffic ...

2023

Spatiotemporal wildfire modeling through point processes with moderate and extreme marks

Jonathan Koh Boon Han

Accurate spatiotemporal modeling of conditions leading to moderate and large wildfires provides better understanding of mechanisms driving fire-prone ecosystems and improves risk management. Here, we develop a joint model for the occurrence intensity and t ...

2023

Distributionally Robust Inverse Covariance Estimation: The Wasserstein Shrinkage Estimator

Daniel Kuhn, Viet Anh Nguyen, Peyman Mohajerin Esfahani

We introduce a distributionally robust maximum likelihood estimation model with a Wasserstein ambiguity set to infer the inverse covariance matrix of a p-dimensional Gaussian random vector from n independent samples. The proposed model minimizes the worst ...

2022

Mismatched Estimation of Non-Symmetric Rank-One Matrices Under Gaussian Noise

Nicolas Macris, Farzad Pourkamali

We consider the estimation of a nxm matrix uv(T) observed through an additive Gaussian noise channel, a problem that frequently arises in statistics and machine learning. We investigate a scenario involving mismatched Bayesian inference in which the stat ...

IEEE2022

Running Speed Estimation Using Shoe-Worn Inertial Sensors: Direct Integration, Linear, and Personalized Model

Kamiar Aminian, Mathieu Pascal Falbriard, Abolfazl Soltani

The overground speed is a key component of running analysis. Today, most speed estimation wearable systems are based on GNSS technology. However, these devices can suffer from sparse communication with the satellites and have a high-power consumption. In t ...

2021

Testing general relativity on cosmological scales at redshift z similar to 1.5 with quasar and CMB lensing

Cheng Zhao

We test general relativity (GR) at the effective redshift (z) over tilde similar to 1.5 by estimating the statistic E-G, a probe of gravity, on cosmological scales 19 - 190 h(-1)Mpc. This is the highest redshift and largest scale estimation of E-G so far. ...

OXFORD UNIV PRESS2021

A general framework for the integration of complex choice models into mixed integer optimization

Meritxell Pacheco Paneque

The objective of this thesis is to develop a general methodology to incorporate a disaggregate demand representation in supply-oriented optimization problems that allows to capture the interplay between the behavior of individuals and the decisions to be o ...

EPFL2020

Accurate Description of Nuclear Quantum Effects with High-Order Perturbed Path Integrals (HOPPI)

Michele Ceriotti, Venkat Kapil

Imaginary time path-integral (PI) simulations that account for nuclear quantum effects (NQE) beyond the harmonic approximation are increasingly employed together with modern electronic-structure calculations. Existing PI methods are applicable to molecules ...

AMER CHEMICAL SOC2020

Consistent Tomography Under Partial Observations Over Adaptive Networks

Ali H. Sayed

This paper studies the problem of inferring whether an agent is directly influenced by another agent over a network. Agent i influences agent j if they are connected (according to the network topology), and if agent j uses the data from agent i to update i ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Does desorption affect the length distributions of nanowires?

Anna Fontcuberta i Morral, Wonjong Kim, Jelena Vukajlovic Plestina

State-of-the art models for statistical properties within the nanowire ensembles consider influx of precursors, reflection and surface diffusion of adatoms. These models predict a delay in the nanowire growth start and the evolution toward an asymmetric le ...

2019