Results 31 to 40 of about 2,749 (228)
Reducing Memory and Computational Cost for Deep Neural Network Training with Quantized Parameter Updates [PDF]
Journal of Universal Computer ScienceFor embedded devices, both memory and computational efficiency are essential due to their constrained resources. However, neural network training remains both computation and memory intensive.
Leo Buron +2 more
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Mathematics, 2021 Most existing flexible count distributions allow only approximate inference when used in a regression context. This work proposes a new framework to provide an exact and flexible alternative for modeling and simulating count data with various types of ...
Chénangnon Frédéric Tovissodé +3 more
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IMA Journal of Numerical Analysis, 2022 Abstract Motivated by the advent of machine learning, the last few years have seen the return of hardware-supported low-precision computing. Computations with fewer digits are faster and more memory and energy efficient but can be extremely susceptible to rounding errors.
Croci, M, Giles, MB
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Direct solution of the Chemical Master Equation using quantized tensor trains. [PDF]
PLoS Computational Biology, 2014 The Chemical Master Equation (CME) is a cornerstone of stochastic analysis and simulation of models of biochemical reaction networks. Yet direct solutions of the CME have remained elusive.
Vladimir Kazeev +3 more
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A comparison of Monte Carlo sampling methods for metabolic network models.
PLoS ONE, 2020 Reaction rates (fluxes) in a metabolic network can be analyzed using constraint-based modeling which imposes a steady state assumption on the system. In a deterministic formulation of the problem the steady state assumption has to be fulfilled exactly ...
Shirin Fallahi +2 more
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Climate‐change modelling at reduced floating‐point precision with stochastic rounding
Quarterly Journal of the Royal Meteorological Society, 2023 AbstractReduced‐precision floating‐point arithmetic is now deployed routinely in numerical weather forecasting over short timescales. However, the applicability of these reduced‐precision techniques to longer‐timescale climate simulations—especially those that seek to describe a dynamical, changing climate—remains unclear.
Kimpson, Tom +3 more
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Resource Allocation With Minimum Outage Probability in Multicarrier Multicast Systems
IEEE Access, 2018 Several innovative applications are emerging that require significant multimedia data transmissions, which unfortunately, current communication systems struggle to provide.
Duc-Phuc Vuong +2 more
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Memory of cell shape biases stochastic fate decision-making despite mitotic rounding
Nature Communications, 2016 Cell shape influences function but during mitotic cell rounding the original shape is lost. Here the authors show that the cellular eccentricity of progenitor cell biases stochastic fate-decisions using a combination of quantitative live imaging, genetic
Takashi Akanuma +4 more
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Coevolving edge rounding and shape of glacial erratics: the case of Shap granite, UK [PDF]
Earth Surface DynamicsThe size distributions and the shapes of detrital rock clasts can shed light on the environmental history of the clast assemblages and the processes responsible for clast comminution.
P. A. Carling
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Limited-Precision Stochastic Rounding
CoRRStochastic rounding (SR) is a probabilistic method used to round numbers to floating-point and fixed-point representations. In length $n$ summation, the worst-case error of SR grows as $\sqrt{n}$ with high probability, unlike for standard modes, like round-to-nearest (RN), which grows as $n$.
El-Mehdi El Arar +3 more
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