🏛️ The physics.comp-ph Crypt
physics.comp-ph: Where physics.comp-ph papers rest without their code.
231
Total Papers
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Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs
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Contemporary machine learning: a guide for practitioners in the physical sciences
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A massively parallel semi-Lagrangian solver for the six-dimensional Vlasov-Poisson equation
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Computationally Efficient CFD Prediction of Bubbly Flow using Physics-Guided Deep Learning
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A Helmholtz equation solver using unsupervised learning: Application to transcranial ultrasound
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Coercing Machine Learning to Output Physically Accurate Results
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Ring artifacts correction in compressed sensing tomographic reconstruction
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Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning
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Deep Density: circumventing the Kohn-Sham equations via symmetry preserving neural networks
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Simulation of unsteady blood flows in a patient-specific compliant pulmonary artery with a highly parallel monolithically coupled fluid-structure interaction algorithm
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Higher-Order Equivariant Neural Networks for Charge Density Prediction in Materials
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GPU coprocessors as a service for deep learning inference in high energy physics
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A reciprocal formulation of non-exponential radiative transfer. 1: Sketch and motivation
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Can Boltzmann Machines Discover Cluster Updates ?
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Reducing hyperparameter dependence by external timescale tailoring
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GPU-accelerated machine learning inference as a service for computing in neutrino experiments
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End-to-End Differentiable Molecular Mechanics Force Field Construction
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Machine learning and serving of discrete field theories -- when artificial intelligence meets the discrete universe
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Extracting local switching fields in permanent magnets using machine learning
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Accelerating finite-rate chemical kinetics with coprocessors: comparing vectorization methods on GPUs, MICs, and CPUs
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Solving Inverse Wave Scattering with Deep Learning
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A kernel-based approach to molecular conformation analysis
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