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🏛️ The physics.comp-ph Crypt
physics.comp-ph: Where physics.comp-ph papers rest without their code.
234
Total Papers
198
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36
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15.4%
Survival Rate
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Deep Potential Molecular Dynamics: a scalable model with the accuracy of quantum mechanics
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Heterogeneous Parallelization and Acceleration of Molecular Dynamics Simulations in GROMACS
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By-passing the Kohn-Sham equations with machine learning
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Machine Learning of coarse-grained Molecular Dynamics Force Fields
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Towards Physics-informed Deep Learning for Turbulent Flow Prediction
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Active Learning of Uniformly Accurate Inter-atomic Potentials for Materials Simulation
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Wave Physics as an Analog Recurrent Neural Network
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A Multi-Threaded Version of MCFM
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Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles
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Multi-level Convolutional Autoencoder Networks for Parametric Prediction of Spatio-temporal Dynamics
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Inferring low-dimensional microstructure representations using convolutional neural networks
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Understanding Kernel Ridge Regression: Common behaviors from simple functions to density functionals
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Global optimization of parameters in the reactive force field ReaxFF for SiOH
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TeaNet: universal neural network interatomic potential inspired by iterative electronic relaxations
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Fast, accurate, and transferable many-body interatomic potentials by symbolic regression
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Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics Problems
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Toward an AI Physicist for Unsupervised Learning
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Fast Uncertainty Estimates in Deep Learning Interatomic Potentials
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Deep-learning of Parametric Partial Differential Equations from Sparse and Noisy Data
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Range entropy: A bridge between signal complexity and self-similarity
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Better, Faster Fermionic Neural Networks
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Enhancement of shock-capturing methods via machine learning
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