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11/08/2022
First principles physics-informed neural network for quantum wavefunctions and eigenvalue surfaces
Physics-informed neural networks have been widely applied to learn gener...
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11/01/2022
Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows
Physics-Informed Neural Networks (PINNs) offer a promising approach to s...
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07/12/2022
RcTorch: a PyTorch Reservoir Computing Package with Automated Hyper-Parameter Optimization
Reservoir computers (RCs) are among the fastest to train of all neural n...
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10/21/2021
One-Shot Transfer Learning of Physics-Informed Neural Networks
Solving differential equations efficiently and accurately sits at the he...
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08/27/2021
Modeling the effect of the vaccination campaign on the Covid-19 pandemic
Population-wide vaccination is critical for containing the SARS-CoV-2 (C...
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08/25/2021
Unsupervised Reservoir Computing for Solving Ordinary Differential Equations
There is a wave of interest in using unsupervised neural networks for so...
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07/16/2021
Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems
Accurately learning the temporal behavior of dynamical systems requires ...
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06/07/2021
Encoding Involutory Invariance in Neural Networks
In certain situations, Neural Networks (NN) are trained upon data that o...
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01/15/2021
A New Artificial Neuron Proposal with Trainable Simultaneous Local and Global Activation Function
The activation function plays a fundamental role in the artificial neura...
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10/10/2020
Unsupervised Neural Networks for Quantum Eigenvalue Problems
Eigenvalue problems are critical to several fields of science and engine...
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10/10/2020
Semi-supervised Neural Networks solve an inverse problem for modeling Covid-19 spread
Studying the dynamics of COVID-19 is of paramount importance to understa...
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01/29/2020