Publications related to Economic forecasting

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

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

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

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

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

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Evann Pierre Guy Courdier

Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power. Simultaneously, a critical pain point arises as several computer vision applications are deploye ...

EPFL2024

Euclid: The search for primordial features

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

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

Toward Reliable Human Pose Forecasting With Uncertainty

Alexandre Massoud Alahi, Saeed Saadatnejad, Taylor Ferdinand Mordan, Parham Saremi

Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence of past observed ones. However, the lack of unified benchmarks and limited ...

2024

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

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

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

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

Optimized numerical solutions of SIRDVW multiage model controlling SARS-CoV-2 vaccine roll out: An application to the Italian scenario

Alfio Quarteroni, Luca Dede', Nicola Parolini

In the context of SARS-CoV-2 pandemic, mathematical modelling has played a funda-mental role for making forecasts, simulating scenarios and evaluating the impact of pre-ventive political, social and pharmaceutical measures. Optimal control theory represent ...

KEAI PUBLISHING LTD2023

Euclid preparation: XXVIII. Forecasts for ten different higher-order weak lensing statistics

Frédéric Courbin, Gianluca Castignani, Austin Chandler Peel, Jean-Luc Starck, Maurizio Martinelli, Yi Wang, Richard Massey, Fabio Finelli, Marcello Farina

Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale ...

EDP SCIENCES S A2023

Semi-analytic forecasts for Roman - the beginning of a new era of deep-wide galaxy surveys

Michaela Hirschmann

The Nancy Grace Roman Space Telescope, NASA's next flagship observatory, will redefine deep-field galaxy survey with a field of view two orders of magnitude larger than Hubble and an angular resolution of matching quality. These future deep-wide galaxy sur ...

OXFORD UNIV PRESS2023

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

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

Ekaterina Krymova, Markus Scholz

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

Numerical Weather Prediction and Artificial Neural Network Coupling for Wind Energy Forecast

Fernando Porté Agel, Jiannong Fang, Lorenzo Donadio

In the past two decades, wind energy has been under fast development worldwide. The dramatic increase of wind power penetration in electricity production has posed a big challenge to grid integration due to the high uncertainty of wind power. Accurate real ...

2021

Secondary ice production in summer clouds over the Antarctic coast: an underappreciated process in atmospheric models

Athanasios Nenes, Alexis Berne, Georgia Sotiropoulou, Etienne Gabriel Henri Vignon

The correct representation of Antarctic clouds in atmospheric models is crucial for accurate projections of the future Antarctic climate. This is particularly true for summer clouds which play a critical role in the surface melting of the ice shelves in th ...

European Geosciences Union2021

Predicting spatial patterns of soil bacteria under current and future environmental conditions

Nicolas Jean Philippe Guex, Jan Roelof van der Meer, Marco Pagni, Aline Buri

Soil bacteria are largely missing from future biodiversity assessments hindering comprehensive forecasts of ecosystem changes. Soil bacterial communities are expected to be more strongly driven by pH and less by other edaphic and climatic factors. Thus, al ...

2021

Waste collection inventory routing with non-stationary stochastic demands

Michel Bierlaire, Sacha Varone, Mohammad Yousef Maknoon, Iliya Dimitrov Markov

We solve a rich routing problem inspired from practice, in which a heterogeneous fixed fleet is used for collecting recyclable waste from large containers over a finite planning horizon. Each container is equipped with a sensor that communicates its level ...

PERGAMON-ELSEVIER SCIENCE LTD2020

Model based forecasting for demand response strategies

Lorenzo Nespoli

The incremental deployment of decentralized renewable energy sources in the distribution grid is triggering a paradigm change for the power sector. This shift from a centralized structure with big power plants to a decentralized scenario of distributed ene ...

EPFL2019

Modelling and Forecasting of Photovoltaic Generation for Microgrid Applications: from Theory to Validation

Enrica Scolari

The penetration of stochastic renewable generation in modern power systems requires to reconsider conventional practices to ensure the reliable functioning of the electrical network. Decentralized control schemes for distributed energy resources (DERs) hav ...

EPFL2019

Information-gap decision theory (IGDT): a new promising method for management of uncertainties in hydropower projects: case study

Anton Schleiss, Felix Oberrauch

The design of hydropower is determined by estimates and long-term forecasts. These forecasts and estimates are highly uncertain and make performance evaluation and design choices challenging. Effective values deviating from the estimates can have a signifi ...

Hydropower&Dams, Aqua Media International2018