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🏛️ The physics.chem-ph Crypt
physics.chem-ph: Where physics.chem-ph papers rest without their code.
117
Total Papers
78
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1
Twilight
38
Has Code
32.5%
Survival Rate
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Information geometric bound on general chemical reaction networks
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Reconstructing Kernel-based Machine Learning Force Fields with Super-linear Convergence
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The Bigger the Better? Accurate Molecular Potential Energy Surfaces from Minimalist Neural Networks
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Efficient interpolation of molecular properties across chemical compound space with low-dimensional descriptors
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Efficient Exploration of Chemical Kinetics
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BoostMD: Accelerating molecular sampling by leveraging ML force field features from previous time-steps
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Implicit Delta Learning of High Fidelity Neural Network Potentials
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Using Restricted Boltzmann Machines to Model Molecular Geometries
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Uncertainty quantification of molecular property prediction using Bayesian neural network models
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On the Statistics of Reaction-Diffusion Simulations for Molecular Communication
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Understanding and eliminating spurious modes in variational Monte Carlo using collective variables
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The MolecularWeb Universe: Web-Based, Immersive, Multiuser Molecular Graphics And Modeling, for Education and Work in Chemistry, Structural Biology, and Materials Sciences
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ILVES: Accurate and efficient bond length and angle constraints in molecular dynamics
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OpenQDC: Open Quantum Data Commons
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Massively parallel quantum chemistry: PFAS on over 1 million cloud vCPUs
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Noisy, sparse, nonlinear: Navigating the Bermuda Triangle of physical inference with deep filtering
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Holistic chemical evaluation reveals pitfalls in reaction prediction models
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Optimizing $CO_{2}$ Capture in Pressure Swing Adsorption Units: A Deep Neural Network Approach with Optimality Evaluation and Operating Maps for Decision-Making
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Transfer learning for predicting source terms of principal component transport in chemically reactive flow
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Deep Learning as a Method for Inversion of NMR Signals
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Coarse-Grained Configurational Polymer Fingerprints for Property Prediction using Machine Learning
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$Δ$-ML Ensembles for Selecting Quantum Chemistry Methods to Compute Intermolecular Interactions
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