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

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

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 ...

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 ...

Snow plays a crucial role in processes regulating ecosystems, the climate, and human development. Mountain snowpack in particular has great relevance for downstream communities. Knowledge about the distribution and properties of the snowpack thus help in p ...

The atmospheric layer adjacent to the earth's surface is of crucial importance for weather models due to the exchange of energy between the surface and the atmosphere. This exchange is dependent on the various surface properties and influences the state of ...

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 ...

Radar rainfall nowcasting has mostly been applied to relatively large (often rural) domains (e.g., river basins), although rainfall nowcasting in small urban areas is expected to be more challenging. Here, we selected 80 events with high rainfall intensiti ...

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 ...

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 ...

The Mountain snowpack stores months of winter precipitation at high elevations, supplying snowmelt to lowland areas in drier seasons for agriculture and human consumption worldwide. Accurate seasonal predictions of the snowpack are thus of great importance ...

The disclosure provides antibodies, or antigen-binding fragments thereof, and use thereof in prophylaxis, treatment and/or attenuation of a SARS-CoV-2 virus infection. ...

Context. The Euclid mission of the European Space Agency will perform a survey of weak lensing cosmic shear and galaxy clustering in order to constrain cosmological models and fundamental physics. Aims. We expand and adjust the mock Euclid likelihoods of t ...

Anthropogenic modification of natural landscapes to urban environments impacts land-atmosphere interactions in the boundary layer. Ample research has demonstrated the effect of such landscape transitions on development of the urban heat island (UHI), but c ...

We focus on distinctive data-driven measures of the fate of ongoing epidemics. The relevance of our pursuit is suggested by recent results proving that the short-term temporal evolution of infection spread is described by an epidemicity index related to th ...

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 ...

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 ...

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 ...

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 ...

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 ...

Autonomous ballooning allows for energy-efficient long-range missions but introduces significant challenges for planning and control algorithms, due to their single degree of actuation: vertical rate control through either buoyancy or vertical thrust. Late ...

Lightning is directly or indirectly responsible for significant human casualties and property damage worldwide. A timely prediction of its occurrence can enable authorities and the public to take necessary precautionary actions resulting in diminishing the ...

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

Chattez avec Graph Search

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

Network time series forecasting in photovoltaics power production

Good enough: Intermediate complexity atmospheric models improve the representation of processes affecting seasonal snow

Turbulence and Heat exchange in the Near-Surface Boundary Layer over Patchy Snow

Euclid: The search for primordial features

Nowcasting of High-Intensity Rainfall for Urban Applications in the Netherlands

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Toward Reliable Human Pose Forecasting With Uncertainty

A seasonal snowpack model forced with dynamically downscaled forcing data resolves hydrologically relevant accumulation patterns

Anti-sars-cov-2 antibodies and use thereof in the treatment of sars-cov-2 infection

Euclid: Validation of the MontePython forecasting tools

Urban boundary-layer flows in complex terrain: Dynamic interactions during a hot and dry summer season in Phoenix, Arizona

Epidemicity indices and reproduction numbers from infectious disease data in connected human populations

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

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

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

Optimizing Sales Forecasting, Inventory, Pricing and Sourcing Decisions

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

Reinforcement Learning for Outdoor Balloon Navigation: A Successful Controller for an Autonomous Balloon

Lightning Nowcasting Using Solely Lightning Data