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Arnold Beckmann
"... Computability in Europe (CiE) is an informal network of European scientists working on computability theory, including its foundations, technical development, and applications. Among the aims of the network is to advance our theoretical understanding of what can and cannot be computed, by any means ..."
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Computability in Europe (CiE) is an informal network of European scientists working on computability theory, including its foundations, technical development, and applications. Among the aims of the network is to advance our theoretical understanding of what can and cannot be computed, by any means of computation. Its scientific vision is broad: computations may be performed with discrete or continuous data by all kinds of algorithms, programs, and machines. Computations may be made by experimenting with any sort of physical system obeying the laws of a physical theory such as Newtonian mechanics, quantum theory, or relativity. Computations may be very general, depending on the foundations of set theory; or very specific, using the combinatorics of finite structures. CiE also works on subjects intimately related to computation, especially theories of data and information, and methods for formal reasoning about computations. The sources of new ideas and methods include practical developments in areas such as neural networks, quantum computation, natural computation, molecular computation, computational learning. Applications are
Segmentation of brain MR images through a hidden Markov random field model and the expectationmaximization algorithm
 IEEE TRANSACTIONS ON MEDICAL. IMAGING
, 2001
"... The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogrambased model, the FM has an intrinsic limi ..."
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Cited by 619 (14 self)
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The finite mixture (FM) model is the most commonly used model for statistical segmentation of brain magnetic resonance (MR) images because of its simple mathematical form and the piecewise constant nature of ideal brain MR images. However, being a histogrambased model, the FM has an intrinsic limitation—no spatial information is taken into account. This causes the FM model to work only on welldefined images with low levels of noise; unfortunately, this is often not the the case due to artifacts such as partial volume effect and bias field distortion. Under these conditions, FM modelbased methods produce unreliable results. In this paper, we propose a novel hidden Markov random field (HMRF) model, which is a stochastic process generated by a MRF whose state sequence cannot be observed directly but which can be indirectly estimated through observations. Mathematically, it can be shown that the FM model is a degenerate version of the HMRF model. The advantage of the HMRF model derives from the way in which the spatial information is encoded through the mutual influences of neighboring sites. Although MRF modeling has been employed in MR image segmentation by other researchers, most reported methods are limited to using MRF as a general prior in an FM modelbased approach. To fit the HMRF model, an EM algorithm is used. We show that by incorporating both the HMRF model and the EM algorithm into a HMRFEM framework, an accurate and robust segmentation can be achieved. More importantly, the HMRFEM framework can easily be combined with other techniques. As an example, we show how the bias field correction algorithm of Guillemaud and Brady (1997) can be incorporated into this framework to achieve a threedimensional fully automated approach for brain MR image segmentation.
Comments on Beckmann’s Uniform Reducts
, 2006
"... These comments refer to Arnold Beckmann’s paper [Bec05]. That paper introduces the notion of the uniform reduct of a propositional proof system, which consists of a collection of ∆0(α) formulas, where α is a unary relation symbol. Here I will define essentially the same thing, but make it a collecti ..."
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These comments refer to Arnold Beckmann’s paper [Bec05]. That paper introduces the notion of the uniform reduct of a propositional proof system, which consists of a collection of ∆0(α) formulas, where α is a unary relation symbol. Here I will define essentially the same thing, but make it a
Bounded Arithmetic
, 2008
"... Definable functions Language of Bounded Arithmetic (BA) Language of first order arithmetic similar to Peano Arithmetic Nonlogical symbols: {0,1,+, ·, ≤} + {.,#,...} x  = length of binary representation of x x#y = 2 x·y  produces polynomial growth rate Arnold Beckmann (joint work with Klaus ..."
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Definable functions Language of Bounded Arithmetic (BA) Language of first order arithmetic similar to Peano Arithmetic Nonlogical symbols: {0,1,+, ·, ≤} + {.,#,...} x  = length of binary representation of x x#y = 2 x·y  produces polynomial growth rate Arnold Beckmann (joint work
Automatic Performance Tuning of Sparse Matrix Kernels
, 2003
"... This dissertation presents an automated system to generate highly efficient, platformadapted implementations of sparse matrix kernels. These computational kernels lie at the heart of diverse applications in scientific computing, engineering, economic modeling, and information retrieval, to name a ..."
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Cited by 76 (7 self)
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This dissertation presents an automated system to generate highly efficient, platformadapted implementations of sparse matrix kernels. These computational kernels lie at the heart of diverse applications in scientific computing, engineering, economic modeling, and information retrieval, to name a few. Informally, sparse kernels are computational operations on matrices whose entries are mostly zero, so that operations with and storage of these zero elements may be eliminated. The challenge in developing highperformance implementations of such kernels is choosing the data structure and code that best exploits the structural properties of the matrixgenerally unknown until application runtimefor highperformance on the underlying machine architecture (e.g., memory hierarchy configuration and CPU pipeline structure). We show that conventional implementations of important sparse kernels like sparse matrixvector multiply (SpMV) have historically run at 10% or less of peak machine speed on cachebased superscalar architectures. Our implementations of SpMV, automatically tuned using a methodology based on empiricalsearch, can by contrast achieve up to 31% of peak machine speed, and can be up to 4 faster.
Association analyses of 249 796 individuals reveal 18 new loci associated with body mass index
, 2010
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The neuropathology of schizophrenia. A critical review of the data and their interpretation
 Brain 122 ( Pt
, 1999
"... Despite a hundred years ’ research, the neuropathology of schizophrenia remains obscure. However, neither can the null hypothesis be sustained—that it is a ‘functional’ psychosis, a disorder with no structural basis. A number of abnormalities have been identified and confirmed by metaanalysis, incl ..."
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Cited by 59 (0 self)
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Despite a hundred years ’ research, the neuropathology of schizophrenia remains obscure. However, neither can the null hypothesis be sustained—that it is a ‘functional’ psychosis, a disorder with no structural basis. A number of abnormalities have been identified and confirmed by metaanalysis, including ventricular enlargement and decreased cerebral (cortical and hippocampal) volume. These are characteristic of schizophrenia as a whole, rather than being restricted to a subtype, and are present in firstepisode, unmedicated patients. There is considerable evidence for preferential involvement of the temporal lobe and moderate evidence for an alteration in normal cerebral asymmetries. There are several candidates for the histological and molecular correlates of the macroscopic features. The probable proximal explanation for decreased cortical volume is reduced neuropil and neuronal size, rather than a loss of neurons. These morphometric changes are in turn suggestive of alterations in synaptic, dendritic and axonal organization, a view supported by immunocytochemical and ultrastructural findings. Pathology in subcortical structures is not well established, apart from dorsal thalamic nuclei, which are smaller and contain fewer neurons. Other cytoarchitectural features of schizophrenia which are often discussed, notably entorhinal cortex heterotopias and hippocampal neuronal disarray, remain to be
Klaus von Haeften Helium clusters
"... Neil Arnold Sprites, elves and blue jets lightning in the upper atmosphere Neil Arnold Plasma influences on the Earth's upper atmosphere Nigel Bannister Adaptive Optics, interferometry and the art of astronomical imaging Nigel Bannister NearEarth Objects Martin Barstow Type Ia Supernovae as p ..."
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Neil Arnold Sprites, elves and blue jets lightning in the upper atmosphere Neil Arnold Plasma influences on the Earth's upper atmosphere Nigel Bannister Adaptive Optics, interferometry and the art of astronomical imaging Nigel Bannister NearEarth Objects Martin Barstow Type Ia Supernovae
Results 1  10
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