Publications related to Statistical Unfolding Of Elementary Particle Spectra: Empirical Bayes Estimation And Bias-Corrected Uncertainty Quantification

Related publications (34)

Overcoming Distribution Shifts and Imbalance Challenges in Representation Learning for Deep Regression Models

Deep learning has shown remarkable potential for industrial applications, particularly in predictive maintenance and condition monitoring. A key challenge in this domain is prognostics, specifically predicting the Remaining Useful Life (RUL) of assets - a ...

EPFL2025

Boosting likelihood learning with event reweighting

Andrea Wulzer, Alfredo Glioti, Siyu Chen

Extracting maximal information from experimental data requires access to the likelihood function, which however is never directly available for complex experiments like those performed at high energy colliders. Theoretical predictions are obtained in this ...

Springer Nature2024

Measurement of the photon polarisation in B+ -> K+ pi- pi+ gamma decays at LHCb

Marie Theres Christin Bachmayer

All physical processes can be described, at a fundamental level, through interactions of elementary particles. The Standard Model of particle physics (SM) describes three of the four known fundamental forces and all of the known elementary particles. The a ...

EPFL2025

Deep learning–based detection of generalized convulsive seizures using a wrist‐worn accelerometer

David Atienza Alonso, Jonathan Dan, Antoine Jérôme Spahr

Objective To develop and validate a wrist‐worn accelerometer‐based, deep‐learning tunable algorithm for the automated detection of generalized or bilateral convulsive seizures (CSs) to be integrated with off‐the‐shelf smartwatches. Methods We conducted a ...

Wiley2025

Analytical and EZmock covariance validation for the DESI 2024 results

Jiaxi Yu, Daniel Felipe Forero Sanchez

The estimation of uncertainties in cosmological parameters is an important challenge in Large-Scale-Structure (LSS) analyses. For standard analyses such as Baryon Acoustic Oscillations (BAO) and Full-Shape two approaches are usually considered. First: anal ...

2025

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Pakshal Narendra Bohra

In inverse problems, the task is to reconstruct an unknown signal from its possibly noise-corrupted measurements. Penalized-likelihood-based estimation and Bayesian estimation are two powerful statistical paradigms for the resolution of such problems. They ...

EPFL2024

Search for $B_{(s)}^{*0}\rightarrow \mu ^+\mu ^-$ in $B_c^+\rightarrow \pi ^+\mu ^+\mu ^-$ decays

Aurelio Bay, Frédéric Blanc, Marie Theres Christin Bachmayer

A search for the very rare

B^{*0}\rightarrow \mu ^+\mu ^-

and

B_{s}^{*0}\rightarrow \mu ^+\mu ^-

decays is conducted by analysing the

B_c^+\rightarrow \pi ^+\mu ^+\mu ^-

process. The analysis uses proton-proton collision data collected with the LHCb ...

Springer Science and Business Media LLC2025

A Method of Moments Estimator for Interacting Particle Systems and their Mean Field Limit

Andrea Zanoni

We study the problem of learning unknown parameters in stochastic interacting particle systems with polynomial drift, interaction, and diffusion functions from the path of one single particle in the system. Our estimator is obtained by solving a linear sys ...

Siam Publications2024

Anthony C Davison and Igor Rodionov's contribution to the Discussion of 'Estimating means of bounded random variables by betting' by Waudby-Smith and Ramdas

Igor Rodionov, Anthony Christopher Davison

We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical problem of estimating a bounded mean. Our approach generalizes and improves on the celebrated Chernoff method, yielding the best closed-form "empirical-Bernstein" CSs and ...

Oxford Univ Press2024

LXXI. Simulations and nonlinearities beyond ΛCDM. 3. Constraints on f(R) models from the photometric primary probes

Frédéric Courbin, Georges Meylan

We study the constraint on f(R) gravity that can be obtained by photometric primary probes of the Euclid mission. Our focus is the dependence of the constraint on the theoretical modelling of the nonlinear matter power spectrum. In the Hu–Sawicki f(R) grav ...

2025

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

Sequential Reasoning with Socially Caused Beliefs

Mert Kayaalp

Machine learning and artificial intelligence methods have achieved remarkable success, matching and even surpassing human capabilities in various complex tasks. However, many demonstrations have generally neglected a critical part of the intelligence that ...

EPFL2025

Search for Scalar Leptoquarks Produced via τ-Lepton-Quark Scattering in pp Collisions at ffiffi s p=13 TeV

Jian Wang, Matthias Finger, Qian Wang, Yiming Li, João Miguel das Neves Duarte, Matthias Wolf, Varun Sharma, Yi Zhang, Tian Cheng, Yixing Chen, Alexis Kalogeropoulos, Ioannis Papadopoulos, Hua Zhang, Siyuan Wang, Xin Chen, Michele Bianco, Sebastiana Gianì, Sun Hee Kim, Rakesh Chawla, Jan Steggemann, Konstantin Androsov, Junqiu Liu, Anna Mascellani, Federica Legger, Matteo Galli, Gabriele Grosso

The first search for scalar leptoquarks produced in z-lepton-quark collisions is presented. It is based on a set of proton-proton collision data recorded with the CMS detector at the LHC at a center-of-mass energy of 13 TeV corresponding to an integrated l ...

Amer Physical Soc2024

A FEM modelling workflow to simulate THM effects in the rock around nuclear waste packages

Matthias Timothee Stanislas Wojnarowicz

High-level waste, stemming from nuclear electricity generation poses significant environmental and safety concerns. Currently, high-level wastes are stored in interim facilities needing constant monitoring and waiting for a definitive solution. Deep geolog ...

EPFL2024

Impact of beam-beam effects on absolute luminosity calibrations at the CERN Large Hadron Collider

Tatiana Pieloni, Claudia Tambasco

At the Large Hadron Collider (LHC), absolute luminosity calibrations obtained by the van der Meer (vdM) method are affected by the mutual electromagnetic interaction of the two beams. The colliding bunches experience relative orbit shifts, as well as optic ...

Springer2024

Fair real-time control of energy storage systems in active distribution networks in the presence of uncertainties

Plouton Grammatikos

The thesis explores the issue of fairness in the real-time (RT) control of battery energy storage systems (BESSs) hosted in active distribution networks (ADNs) in the presence of uncertainties by proposing and experimentally validating appropriate control ...

EPFL2024

Search for the lepton flavour violating decays B0→e±μ∓ and B0s→e±μ∓ with LHCb Run 2 data

Sebastian Schulte

A large variety of new physics models suggest that the rates for lepton flavour violating

b

-hadron decays may be much higher than predicted in the Standard Model, which leads to a high interest in the search for such decays. This thesis presents the se ...

EPFL2024

Design of an Open-Loop Pile-Oscillation Program in the CROCUS Reactor

Andreas Pautz, Vincent Pierre Lamirand, Axel Guy Marie Laureau, Thomas Jean-François Ligonnet

As a follow-up to the CEA-EPFL PETALE experimental program on stainless steel nuclear data, the EPFL initiated an open-loop pile-oscillation experimental program in the CROCUS reactor: BLOOM. A reproduction of the critical experiments of PETALE, the progra ...

2024

ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

Minh Hieu Lê, Nikita Durasov

Whereas the ability of deep networks to produce useful predictions on many kinds of data has been amply demonstrated, estimating the reliability of these predictions remains challenging. Sampling approaches such as MC-Dropout and Deep Ensembles have emerge ...

2024

Studies of crystal collimation for heavy ion operation at the LHC

Rongrong Cai

At CERN's Large Hadron Collider (LHC), proton and heavy-ion beams are accelerated to multi-TeV energies to be collided for the needs of the scientific community around the world. The total stored beam energy of tens to hundreds ofMJ creates potential threa ...

EPFL2024