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检索条件"主题词=Differentiable Programming"
96 条 记 录,以下是1-10 订阅
Closing the gap between SGP4 and high-precision propagation via differentiable programming
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ACTA ASTRONAUTICA 2025年 226卷 694-701页
作者: Acciarini, Giacomo Baydin, Atilim Gunes Izzo, Dario Univ Surrey Surrey Space Ctr Stag HillUniv Campus Guildford GU2 7XH England European Space Agcy Adv Concepts Team Keplerlaan 1 NL-2201 AZ Noordwijk Netherlands Univ Oxford Dept Comp Sci Parks Rd Oxford OX1 3PJ England
The simplified general perturbations 4 (SGP4) orbital propagation model is one of the most widely used methods for rapidly and reliably predicting the positions and velocities of objects orbiting Earth. Over time, SGP... 详细信息
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THB-DiFF: a GPU-accelerated differentiable programming framework for THB-splines
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ENGINEERING WITH COMPUTERS 2024年 第6期40卷 3477-3493页
作者: Moola, Ajith Balu, Aditya Krishnamurthy, Adarsh Pawar, Aishwarya Iowa State Univ Ames IA USA
We have developed a differentiable programming framework for truncated hierarchical B-splines (THB-splines), which can be used for several applications in geometry modeling, such as surface fitting and deformable imag... 详细信息
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Neural-Integrated Meshfree (NIM) Method: A differentiable programming-based hybrid solver for computational mechanics
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COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2024年 427卷
作者: Du, Honghui He, Qizhi Univ Minnesota Dept Civil Environm & Geoengn 500 Pillsbury Dr SE Minneapolis MN 55455 USA
While deep learning and data -driven modeling approaches based on deep neural networks (DNNs) have recently attracted increasing attention for solving partial differential equations, their practical applications to re... 详细信息
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differentiable programming and density matrix based Hartree–Fock method
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Chinese Physics B 2021年 第6期30卷 249-254页
作者: Hong-Bin Ren Lei Wang Xi Dai Beijing National Laboratory for Condensed Matter Physics and Institute of Physics Chinese Academy of SciencesBeijing 100190China School of Physical Sciences University of Chinese Academy of SciencesBeijing 100049China Songshan Lake Materials Laboratory Dongguan 523808China Department of Physics Hong Kong University of Science and TechnologyClear Water BayKowloon 999077Hong KongChina
differentiable programming is an emerging programming paradigm that allows people to take derivative of an output of arbitrary code snippet with respect to its input. It is the workhorse behind several well known deep... 详细信息
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differentiable programming for functional connectomics  2
Differentiable programming for functional connectomics
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2nd Machine Learning for Health (ML4H) Symposium
作者: Ciric, Rastko Thomas, Armin W. Esteban, Oscar Poldrack, Russell A. Stanford Univ Dept Bioengn Stanford CA 94305 USA Stanford Univ Stanford Data Sci Stanford CA USA Univ Lausanne Dept Radiol Lausanne Switzerland Stanford Univ Dept Psychol Stanford CA USA
Mapping the functional connectome has the potential to uncover key insights into brain organisation. However, existing workflows for functional connectomics are limited in their adaptability to new data, and principle... 详细信息
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differentiable programming A LA MOREAU  47
DIFFERENTIABLE PROGRAMMING A LA MOREAU
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47th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
作者: Roulet, Vincent Harchaoui, Zaid Univ Washington Dept Stat Seattle WA 98195 USA
The notion of a Moreau envelope is central to the analysis of first-order optimization algorithms for machine learning and signal processing. We define a compositional calculus adapted to Moreau envelopes and show how... 详细信息
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LAGrad: Statically Optimized differentiable programming in MLIR  2023
LAGrad: Statically Optimized Differentiable Programming in M...
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32nd ACM SIGPLAN International Conference on Compiler Construction (CC)
作者: Peng, Mai Jacob Dubach, Christophe McGill Univ Montreal PQ Canada Mila Montreal PQ Canada
Automatic differentiation (AD) is a central algorithm in deep learning and the emerging field of differentiable programming. However, the performance of AD remains a significant bottleneck in these fields. Training la... 详细信息
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Primal-Dual differentiable programming for Distribution System Critical Load Restoration
Primal-Dual Differentiable Programming for Distribution Syst...
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IEEE-Power-and-Energy-Society General Meeting (PESGM)
作者: Zhang, Xiangyu Knueven, Bernard Zamzam, Ahmed Reynolds, Matthew Jones, Wesley
Swift and reliable critical load restoration (CLR) can help make a distribution system resilient towards extreme events. To optimally achieve that, alongside practical concerns such as limiting online computational bu... 详细信息
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Novel machine learning and differentiable programming techniques applied to the VIP-2 underground experiment
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MEASUREMENT SCIENCE AND TECHNOLOGY 2024年 第2期35卷 025501-025501页
作者: Napolitano, Fabrizio Bazzi, Massimiliano Bragadireanu, Mario Cargnelli, Michael Clozza, Alberto De Paolis, Luca Del Grande, Raffaele Fiorini, Carlo Guaraldo, Carlo Iliescu, Mihail Laubenstein, Matthias Manti, Simone Marton, Johann Miliucci, Marco Piscicchia, Kristian Porcelli, Alessio Scordo, Alessandro Sgaramella, Francesco Sirghi, Diana Laura Sirghi, Florin Doce, Oton Vazquez Zmeskal, Johann Curceanu, Catalina INFN Lab Nazl Frascati Via E Fermi 54 I-00044 Frascati Rome Italy IFIN HH Inst Natl Pentru Fiz Inginerie Nucl Horia Hulubei Str Atomistilor 407 Bucharest Romania Stefan Meyer Inst Subatom Phys Austrian Acad Sci Kegelgasse 27 A-1030 Vienna Austria Tech Univ Munich Phys Dept E62 James Franck Str 1 D-85748 Garching Germany Dipartimento Elettron Informaz & Bioingn Politecn Milano I-20133 Milan Italy INFN Sez Milano I-20133 Milan Italy INFN Lab Nazl Gran Sasso Via G Acitelli 22 I-67100 Assergi Laquila Italy Ctr Ric Enr Fermi Museo Stor Fis Ctr Studi & Ric Enr Fermi Via Panisperna 89a I-00184 Rome Roma Italy Italian Space Agcy Via PolitecnS n c I-00133 Rome Roma Italy
In this work, we present novel machine learning and differentiable programming enhanced calibration techniques used to improve the energy resolution of the Silicon Drift Detectors (SDDs) of the VIP-2 underground exper... 详细信息
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Learning closure relations using differentiable programming: An example in radiation transport
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JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER 2024年 318卷
作者: Crilly, A. J. Duhig, B. Bouziani, N. Imperial Coll Ctr Inertial Fus Studies Blackett Lab London SW7 2AZ England Imperial Coll London I X Ctr AI Sci White City Campus84 Wood Lane London W12 0BZ England Imperial Coll Dept Math London SW7 2AZ England
Reduced order models with a-priori unknown closure relations are ubiquitous in transport problems. In this work, we present a machine-learning approach to finding closure relations utilising differentiable programming... 详细信息
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