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Lior Horesh
Lior Horesh
IBM TJ Watson Research Center | Columbia University
Верификована је имејл адреса на us.ibm.com - Почетна страница
Наслов
Навело
Навело
Година
Leveraging Secondary Storage to Simulate Deep 54-qubit Sycamore Circuits
E Pednault, JA Gunnels, G Nannicini, L Horesh, R Wisnieff
https://arxiv.org/abs/1910.09534, 2019
2312019
Pareto-Efficient Quantum Circuit Simulation Using Tensor Contraction Deferral
E Pednault, JA Gunnels, G Nannicini, L Horesh, T Magerlein, ...
https://arxiv.org/abs/1710.05867, 2017
212*2017
Multi-frequency electrical impedance tomography (EIT) of the adult human head: initial findings in brain tumours, arteriovenous malformations and chronic stroke, development of …
A Romsauerova, A McEwan, L Horesh, R Yerworth, RH Bayford, ...
Physiological measurement 27 (5), S147, 2006
1742006
Numerical methods for experimental design of large-scale linear ill-posed inverse problems
E Haber, L Horesh, L Tenorio
Inverse Problems 24 (5), 055012, 2008
1622008
Use of anisotropic modelling in electrical impedance tomography; description of method and preliminary assessment of utility in imaging brain function in the adult human head
JFPJ Abascal, SR Arridge, D Atkinson, R Horesh, L Fabrizi, M De Lucia, ...
Neuroimage 43 (2), 258-268, 2008
1562008
Design and calibration of a compact multi-frequency EIT system for acute stroke imaging
A McEwan, A Romsauerova, R Yerworth, L Horesh, R Bayford, D Holder
Physiological measurement 27 (5), S199, 2006
1492006
Thinking Fast and Slow in AI
G Booch, F Fabiano, L Horesh, K Kate, J Lenchner, N Linck, A Loreggia, ...
Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 2021
1242021
Generating accurate finite element meshes for the forward model of the human head in EIT
A Tizzard, L Horesh, RJ Yerworth, DS Holder, RH Bayford
Physiological measurement 26 (2), S251, 2005
1122005
Tensor-tensor algebra for optimal representation and compression of multiway data
ME Kilmer, L Horesh, H Avron, E Newman
Proceedings of the National Academy of Science (PNAS) 118 (28), e2015851118, 2021
108*2021
Factors limiting the application of electrical impedance tomography for identification of regional conductivity changes using scalp electrodes during epileptic seizures in humans
L Fabrizi, M Sparkes, L Horesh, JFPJ Abascal, A McEwan, RH Bayford, ...
Physiological measurement 27 (5), S163, 2006
962006
Numerical methods for the design of large-scale nonlinear discrete ill-posed inverse problems
E Haber, L Horesh, L Tenorio
Inverse Problems 26 (2), 025002, 2009
952009
Some novel approaches in modelling and image reconstruction for multi-frequency electrical impedance tomography of the human brain
L Horesh
PQDT-Global, 2006
902006
Diffuse photon propagation in multilayered geometries
J Sikora, A Zacharopoulos, A Douiri, M Schweiger, L Horesh, SR Arridge, ...
Physics in Medicine & Biology 51 (3), 497, 2006
882006
Design of electrodes and current limits for low frequency electrical impedance tomography of the brain
O Gilad, L Horesh, DS Holder
Medical & biological engineering & computing 45, 621-633, 2007
872007
Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning
S Lu, K Zhang, T Chen, T Baser, L Horesh
Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21), 2021
742021
Plansformer: Generating symbolic plans using transformers
V Pallagani, B Muppasani, K Murugesan, F Rossi, L Horesh, B Srivastava, ...
arXiv preprint arXiv:2212.08681, 2022
592022
Combining data and theory for derivable scientific discovery with AI-Descartes
C Cornelio, S Dash, V Austel, TR Josephson, J Goncalves, KL Clarkson, ...
Nature Communications 14 (1), 1777, 2023
572023
A second order discretization of Maxwell's equations in the quasi-static regime on OcTree grids
L Horesh, E Haber
SIAM Journal on Scientific Computing 33 (5), 2805-2822, 2011
562011
Optimal experimental design for the large‐scale nonlinear ill‐posed problem of impedance imaging
L Horesh, E Haber, L Tenorio
Large‐Scale Inverse Problems and Quantification of Uncertainty, 273-290, 2010
552010
Stable Tensor Neural Networks for Rapid Deep Learning
E Newman, L Horesh, H Avron, M Kilmer
https://arxiv.org/abs/1811.06569, 2018
512018
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