FASTCUDA: Open Source FPGA Accelerator & Hardware-Software Codesign Toolset for CUDA Kernels [PDF]
, 2012 Using FPGAs as hardware accelerators that communicate with a central CPU is becoming a common practice in the embedded design world but there is no standard methodology and toolset to facilitate this path yet.
I. Papaefstathiou +20 more
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Time fractional Yang-Abdel-Cattani derivative in generalized MHD Casson fluid flow with heat source and chemical reaction. [PDF]
Sci Rep, 2023 Sehra, Sadia H, Haq SU, Khan I.
europepmc +1 more source
General Non-Markovian Quantum Dynamics. [PDF]
Entropy (Basel), 2021 Tarasov VE.
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Overdosing with apricot kernels – seriously?
, 2019 Dear Sir, Psychiatrists reading RANZCP journals may not be aware of risks posed by stone fruit, in particular apricot kernels. This letter aims to educate psychiatrists on the risks of cyanide poisoning from apricot kernels.
Gleadow, R, Beckmann, KM
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String kernels, Fisher kernels and finite state automata
, 2003 In this paper we show how the generation of documents can be thought of as a k-stage Markov process, which leads to a Fisher kernel from which the n-gram and string kernels can be re-constructed.
Shawe-Taylor, John +2 more
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Prolate spheroidal wave functions, Sonine spaces, and the Riemann zeta function [PDF]
, 2012 In this paper we study underlying spaces associated with A. Connesʼ trace formula (see Connes (1999) [3], Li (2010) [14]). In particular the explicit formula in the theory of prime numbers is expressed as the trace of an operator acting on a Hilbert ...
Li, Xian-Jin, Xian-Jin Li
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Online learning with (multiple) kernels : a review [PDF]
, 2013 This review examines kernel methods for online learning, in particular, multiclass classification. We examine margin-based approaches, stemming from Rosenblatt's original perceptron algorithm, as well as nonparametric probabilistic approaches that are ...
Diethe, Tom, Girolami, Mark
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Variance bounding and geometric ergodicity of Markov chain Monte Carlo kernels for approximate Bayesian computation [PDF]
, 2014 Approximate Bayesian computation has emerged as a standard computational tool when dealing with intractable likelihood functions in Bayesian inference. We show that many common Markov chain Monte Carlo kernels used to facilitate inference in this setting
Łatuszyński, Krzysztof, Lee, Anthony
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Symbols of Pseudodifferential Operators Associated to Gevrey Kernel's Type [PDF]
, 2003 In this article, we aim at proving the truthfulness of the inverse Theorem (1) of [5]. More precisely, we associated symbols of Gevrey type to pseudodifferential operators when the latter are given by their kernels.
Hazi, Mohammed
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Canonical Higher-Order Kernels for Density Derivative Estimation [PDF]
In this note we present r th order kernel density derivative estimators using canonical higher-order kernels. These canonical rescalings uncouple the choice of kernel and scale factor. This approach is useful for selection of the order of the kernel in a
Christopher F. Parmeter +1 more
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