Results 291 to 300 of about 26,173,429 (328)

EMG matching for muscle modelling

Gait & Posture, 2021
Christian, Wyss, Reinald, Brunner
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One Step Diffusion via Shortcut Models

International Conference on Learning Representations
Diffusion models and flow-matching models have enabled generating diverse and realistic images by learning to transfer noise to data. However, sampling from these models involves iterative denoising over many neural network passes, making generation slow
Kevin Frans, Danijar Hafner, Sergey Levine, Pieter Abbeel   +3 more
semanticscholar   +1 more source

Nonlinear strong model matching

IEEE Transactions on Automatic Control, 1990
The problem of matching a given input-output behavior for systems described by general nonlinear differential equations is considered. It is shown that, by appropriately modifying the zero-dynamics algorithm, it is possible to obtain a simple, necessary, and sufficient condition for the solvability of the model matching problem, which requires that the
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Instruction Matching and Modeling

2007
Creating a custom processor that is application-specific is an onerous task upon a designer, who constantly has to ask whether the resulting design is optimal. To obtain such an optimal design is an NP-hard problem, made more time consuming because of the numerous combinations of available parts that make up the processor.
Parameswaran, Sri, Henkel, Jörg, Cheung, Newton   +2 more
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Matching labor's share in a search and matching model [PDF]

, 2011
In the United States, labor’s share of income falls after a positive disturbance to productivity growth or inflation, and it remains low for some time. Previous researchers have argued that the negative relationship between productivity growth and labor’s share is puzzling. I argue otherwise.
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Meta-matching as a simple framework to translate phenotypic predictive models from big to small data

Nature Neuroscience, 2022
Tong He, Lijun An, Jianzhong Chen
exaly  

What can a New Keynesian labor matching model match?

2009
A labor matching model with nominal rigidities can match short-run movements in labor's share with some success. However, it cannot explain much of the behavior of employment, vacancies, and job flows in postwar US data without resorting to additional shocks beyond monetary policy and productivity shocks. In particular, the model suggests that monetary
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Learning Models that Match

 Contrastive learning has emerged as a critical methodology in machine learning applications, offering a pair-wise comparison perspective on data interpretation and model training. This thesis comprehensively examines contrastive learning models, emphasizing their development, application, and optimization for real-world scenarios.
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Model Matching

2007
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Matching Models: Empirics

2009
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