Publications associées à Model-free computation of ultra-short-term prediction intervals of solar irradiance

Challenges of COVID-19 Case Forecasting in the US, 2020-2021

Joseph Chadi Benoit Lemaitre, Pan Xu, Myungjin Kim, Shan Yu, Lei Gao, Weitong Zhang, Wei Cao, Xinyi Li

During the COVID-19 pandemic, forecasting COVID-19 trends to support planning and response was a priority for scientists and decision makers alike. In the United States, COVID-19 forecasting was coordinated by a large group of universities, companies, and ...

Public Library Science2024

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

Anthony Christopher Davison, Igor Rodionov

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

Towards Motion Forecasting with Real-World Perception Inputs: Are End-to-End Approaches Competitive?

Alexandre Massoud Alahi

Motion forecasting is crucial in enabling autonomous vehicles to anticipate the future trajectories of surrounding agents. To do so, it requires solving mapping, detection, tracking, and then forecasting problems, in a multi-step pipeline. In this complex ...

2024

Euclid: The search for primordial features

Georges Meylan, Frédéric Courbin, Fabio Finelli, Richard Massey, Marcello Farina, Yiming Li, Yi Wang

Primordial features, in particular oscillatory signals, imprinted in the primordial power spectrum of density perturbations represent a clear window of opportunity for detecting new physics at high-energy scales. Future spectroscopic and photometric measur ...

Edp Sciences S A2024

Network time series forecasting in photovoltaics power production

Jelena Simeunovic

Accurate forecasting of photovoltaic (PV) power production is crucial for the integration of more renewable energy sources into the power grid. PV power production is highly intermittent, due to the stochastic cloud behaviour and cloud dynamics. Previous w ...

EPFL2024

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Nicola Parolini, Ntorina Thanou, David Kraus, Andrea Kraus, Daniel Lopez, Markus Scholz, Benjamin Bejar Haro, Daniel Rodrigo Lopez, Ekaterina Krymova, Tao Sun

Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive p ...

eLIFE SCIENCES PUBL LTD2023

Improved extended-range prediction of persistent stratospheric perturbations using machine learning

Raphaël Gérard Théodore Michel Marie de Deloÿe et Fourcade de Fondeville, Guillaume Romain Obozinski

On average every 2 years, the stratospheric polar vortex exhibits extreme perturbations known as sudden stratospheric warmings (SSWs). The impact of these events is not limited to the stratosphere: but they can also influence the weather at the surface of ...

Copernicus Gesellschaft Mbh2023

Optimizing Sales Forecasting, Inventory, Pricing and Sourcing Decisions

Yara Kayyali El Alem

In this thesis we address various factors that contribute both theoretically and practically to mitigating supply demand mismatches. The thesis is composed of three chapters, where each chapter is an independent scientific paper. In the first paper, we dev ...

EPFL2023

Maximum likelihood bolometry for ASDEX upgrade experiments

Olivier Claude Martin Février, Riccardo Rossi

Bolometry is an essential diagnostic for calculating the power balances and for the understanding of different physical aspects of tokamak experiments. The reconstruction method based on the Maximum Likelihood (ML) principle, developed initially for JET, h ...

Iop Publishing Ltd2023

Environmental determinants of access to shared sanitation in informal settlements: a cross-sectional study in Abidjan and Nairobi

Jérôme Chenal, Vitor Pessoa Colombo, Jürg Utzinger

Background Universal access to basic sanitation remains a global challenge, particularly in low- and middle-income countries. Efforts are underway to improve access to sanitation in informal settlements, often through shared facilities. However, access to ...

2023

Leukocyte Count and Coronary Artery Disease Events in People With Human Immunodeficiency Virus: A Longitudinal Study

Jacques Fellay, Christian Axel Wandall Thorball

Leukocyte count is associated with coronary artery disease (CAD) events in the general population. Here we show that leukocytes are independently associated with CAD events in people with HIV in Switzerland, after adjusting for traditional and HIVrelated r ...

OXFORD UNIV PRESS INC2023

Search for new heavy resonances decaying to WW, WZ, ZZ, WH, or ZH boson pairs in the all-jets final state in proton-proton collisions at √s=13 TeV

Rakesh Chawla, Andrea Rizzi, Matthias Finger, Federica Legger, Matteo Galli, Sun Hee Kim, Jian Zhao, João Miguel das Neves Duarte, Tagir Aushev, Hua Zhang, Alexis Kalogeropoulos, Yixing Chen, Tian Cheng, Ioannis Papadopoulos, Gabriele Grosso, Valérie Scheurer, Meng Xiao, Qian Wang, Michele Bianco, Varun Sharma, Joao Varela, Sourav Sen, Ashish Sharma, Seungkyu Ha, David Vannerom, Csaba Hajdu, Sanjeev Kumar, Sebastiana Gianì, Kun Shi, Abhisek Datta, Miao Hu, Siyuan Wang, Muhammad Waqas, Anton Petrov, Jian Wang, Yi Zhang, Lei Zhang, Muhammad Ansar Iqbal, Yong Yang, Xin Sun, Muhammad Ahmad, , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Modeling local thermal responses of individuals: Validation of advanced human thermo-physiology models

Dolaana Khovalyg, Mohamad Rida

Human thermo-physiology models (HTPM) are useful tools to assess dynamic and non-uniform human thermal states. However, they are developed based on the physiological data of an average person. In this paper, we present a detailed evaluation of two sophisti ...

2023

Deep Generative Models for Autonomous Driving: from Motion Forecasting to Realistic Image Synthesis

Saeed Saadatnejad

Forecasting is a capability inherent in humans when navigating. Humans routinely plan their paths, considering the potential future movements of those around them. Similarly, to achieve comparable sophistication and safety, autonomous systems must embrace ...

EPFL2023

Quantization for Decentralized Learning Under Subspace Constraints

Ali H. Sayed, Roula Nassif, Stefan Vlaski, Marco Carpentiero

In this article, we consider decentralized optimization problems where agents have individual cost functions to minimize subject to subspace constraints that require the minimizers across the network to lie in low-dimensional subspaces. This constrained fo ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

A note on universal inference

Anthony Christopher Davison, Timmy Rong Tian Tse

Universal inference enables the construction of confidence intervals and tests without regularity conditions by splitting the data into two parts and appealing to Markov's inequality. Previous investigations have shown that the cost of this generality is a ...

WILEY2022

National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021

Markus Scholz, Ekaterina Krymova

Background During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases an ...

Springernature2022

Is There a Cap on Longevity? A Statistical Review

Anthony Christopher Davison, Léo Raymond-Belzile

There is sustained and widespread interest in understanding the limit, if there is any, to the human life span. Apart from its intrinsic and biological interest, changes in survival in old age have implications for the sustainability of social security sys ...

ANNUAL REVIEWS2022

A Machine Learning-based Framework for Forecasting Sales of New Products With Short Life Cycles Using Deep Neural Networks

Ralf Seifert, Yara Kayyali El Alem

Demand forecasting is becoming increasingly important as firms launch new products with short life cycles more frequently. This paper provides a framework based on state-of-the-art techniques that enables firms to use quantitative methods to forecast sales ...

2022

Multivariate time series forecasting for freeway networks

Semin Kwak

This dissertation introduces traffic forecasting methods for different network configurations and data availability. Chapter 2 focuses on single freeway cases. Although its topology is simple, the non-linearity of traffic features makes this prediction sti ...

EPFL2022