Kamu erişimi zorunlu olan makaleler - Lior HoreshDaha fazla bilgi edinin
Bir yerde sunuluyor: 18
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
Zorunlu olanlar: US Department of Energy
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
Zorunlu olanlar: US National Science Foundation
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
Zorunlu olanlar: US Department of Defense, AIRC Foundation for Cancer Research in Italy
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
Zorunlu olanlar: US Department of Energy, US Department of Defense
Dynamic Graph Convolutional Networks Using the Tensor M-Product
O Malik, S Ubaru, L Horesh, M Kilmer, H Avron
SIAM International Conference on Data Mining (SDM 21), 2021
Zorunlu olanlar: US National Science Foundation
Thinking Fast and Slow in AI: the Role of Metacognition
M Ganapini, M Campbell, F Fabiano, L Horesh, J Lenchner, A Loreggia, ...
ACAIN 2022, 2022
Zorunlu olanlar: US National Science Foundation
Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra
N Chepurko, KL Clarkson, L Horesh, H Lin, DP Woodruff
ICML, 2022
Zorunlu olanlar: US National Science Foundation
Hamiltonian Engineering with Constrained Optimization for Quantum Sensing and Control
MF O'Keeffe, L Horesh, DA Braje, IL Chuang
New J. Phys. 21 (023015), 2019
Zorunlu olanlar: US Department of Defense
Image classification using local tensor singular value decompositions
E Newman, M Kilmer, L Horesh
IEEE CAMSAP, 2017
Zorunlu olanlar: US National Science Foundation, US Department of Defense, US Office of the …
A stochastic linearized augmented lagrangian method for decentralized bilevel optimization
S Lu, S Zeng, X Cui, M Squillante, L Horesh, B Kingsbury, J Liu, M Hong
Advances in Neural Information Processing Systems 35, 30638-30650, 2022
Zorunlu olanlar: US National Science Foundation
Distributed adversarial training to robustify deep neural networks at scale
G Zhang, S Lu, Y Zhang, X Chen, PY Chen, Q Fan, L Martie, L Horesh, ...
arXiv preprint arXiv:2206.06257, 2022
Zorunlu olanlar: US National Science Foundation
Experimental design for nonparametric correction of misspecified dynamical models
G Shulkind, L Horesh, H Avron
SIAM/ASA Journal on Uncertainty Quantification 6 (2), 880-906, 2018
Zorunlu olanlar: US Department of Defense
A modelling study to inform specification and optimal electrode placement for imaging of neuronal depolarization during visual evoked responses by electrical and magnetic …
O Gilad, L Horesh, DS Holder
Physiological Measurement 30 (6), S201, 2009
Zorunlu olanlar: US National Institutes of Health
Representation of the fermionic boundary operator
IY Akhalwaya, YH He, L Horesh, V Jejjala, W Kirby, K Naidoo, S Ubaru
Physical Review A 106 (2), 022407, 2022
Zorunlu olanlar: US National Science Foundation, UK Science and Technology Facilities Council …
Fast randomized non-Hermitian eigensolvers based on rational filtering and matrix partitioning
V Kalantzis, Y Xi, L Horesh
SIAM Journal on Scientific Computing 43 (5), S791-S815, 2021
Zorunlu olanlar: US National Science Foundation
On Quantum Algorithms for Random Walks in the Nonnegative Quarter Plane
V Kalantzis, MS Squillante, S Ubaru, L Horesh
MAMA workshop in conjunction with ACM SIGMETRICS / IFIP Performance 2022 …, 2022
Zorunlu olanlar: US Department of Defense
Don't Count the Shots, Make the Shots Count: Efficient Quantum Computation of the Fermionic Boundary Operator
IY Akhalwaya, YH He, L Horesh, V Jejjala, W Kirby, K Naidoo, S Ubaru
arXiv preprint arXiv:2201.11510, 2022
Zorunlu olanlar: US National Science Foundation, UK Science and Technology Facilities Council …
Combining Fast and Slow Thinking for Human-like and Efficient Decisions in Constrained Environments
M Bergamaschi Ganapini, M Campbell, F Fabiano, L Horesh, J Lenchner, ...
Proceedings of the 16th International Workshop on Neural-Symbolic Learning …, 2022
Zorunlu olanlar: US National Science Foundation
Yayıncılık ve maddi kaynak bilgileri otomatik olarak bir bilgisayar programı tarafından belirlenmektedir