Concept

Empirisme

Publications associées (63)

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Hybrid ground-state quantum algorithms based on neural Schrödinger forging

Giuseppe Carleo, Sofia Vallecorsa

Entanglement forging based variational algorithms leverage the bipartition of quantum systems for addressing ground-state problems. The primary limitation of these approaches lies in the exponential summation required over the numerous potential basis stat ...

Amer Physical Soc2024

SIMPLE HIERARCHICAL PLANNING WITH DIFFUSION

Caglar Gulcehre, Chang Chen

Diffusion-based generative methods have proven effective in modeling trajectories with offline datasets. However, they often face computational challenges and can falter in generalization, especially in capturing temporal abstractions for long- horizon tas ...

2024

Imai et al.(IJGHS) have conducted a timely experiment on evaluating a decision support algorithm. However, we are concerned by their choice of estimands which, even if they appear plausible at first, rely on notions and assumptions for which we cannot ever ...

2023

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Knots are the weakest link in surgical sutures, serving as mechanical ligatures between filaments. Exceeding their safe operational limits can cause fatal complications. The empirical nature of present guidelines calls for a predictive understanding of the ...

AMER ASSOC ADVANCEMENT SCIENCE2023

This paper tackles Avalanche Risks Management (ARM), nominated by Switzerland and Austria and inscribed on the UNESCO Representative List of Intangible Cultural Heritage in 2018. On the one hand, this nomination conventionally highlights how traditional em ...

2023

Accurate equilibrium-based interlaminar stress recovery for isogeometric laminated composite Kirchhoff plates

Pablo Antolin Sanchez, Alessandro Reali

Despite the accelerated deployment of laminated composites in a wide variety of markets due to their peculiar engineering features, the design of those materials is often restrained by the lack of cost-efficient modeling techniques. In fact, the existing s ...

ELSEVIER SCI LTD2021

Consensus Control for Decentralized Deep Learning

Martin Jaggi, Sebastian Urban Stich, Anastasiia Koloskova, Tao Lin, Lingjing Kong

Decentralized training of deep learning models enables on-device learning over networks, as well as efficient scaling to large compute clusters. Experiments in earlier works reveal that, even in a data-center setup, decentralized training often suffers fro ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2021

Local theories of consciousness state that one is conscious of a feature if it is adequately represented and processed in sensory brain areas, given some background conditions. We challenge the core prediction of local theories based on long-lasting postdi ...

WILEY2021

Continual Learning for Natural Language Generation in Task-oriented Dialog Systems

Boi Faltings, Mengjie Zhao, Fei Mi, Liangwei Chen

Natural language generation (NLG) is an essential component of task-oriented dialog systems. Despite the recent success of neural approaches for NLG, they are typically developed in an offline manner for particular domains. To better fit real-life applicat ...

2021

The organisation of science: topics, incentives and funding.

Omar Ballester Gonzalez

Ever since the links between the development of new technologies and economic growth became evident, researchers have attempted to study how the creation of knowledge fosters progress. If pushing the frontier of knowledge has an impact on progress and well ...

EPFL2020