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Found 6 papers, 2 papers with code
On the generalization ability of coarse-grained molecular dynamics models for non-equilibrium processes
While a CG model can be constructed by projecting the full dynamics onto a set of resolved variables, the dynamics of the CG variables can recover the full dynamics only when the conditional distribution of the unresolved variables is close to the one associated with the particular projection operator.
Consensus-based construction of high-dimensional free energy surface
One essential problem in quantifying the collective behaviors of molecular systems lies in the accurate construction of free energy surfaces (FESs).
Reproducing Activation Function for Deep Learning
We propose reproducing activation functions (RAFs) to improve deep learning accuracy for various applications ranging from computer vision to scientific computing.
Enforcing exact boundary and initial conditions in the deep mixed residual method
In theory, boundary and initial conditions are important for the wellposedness of partial differential equations (PDEs).
Numerical Analysis Numerical Analysis
Quasi-Monte Carlo sampling for machine-learning partial differential equations
Often, a deep neural network outperforms classical numerical methods in terms of both accuracy and efficiency.
A QMC-deep learning method for diffusivity estimation in random domains
Exciton diffusion plays a vital role in the function of many organic semiconducting opto-electronic devices, where an accurate description requires precise control of heterojunctions.
