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08/31/2023
Artificial to Spiking Neural Networks Conversion for Scientific Machine Learning
We introduce a method to convert Physics-Informed Neural Networks (PINNs...
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07/18/2023
DiTTO: Diffusion-inspired Temporal Transformer Operator
Solving partial differential equations (PDEs) using a data-driven approa...
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06/27/2023
CrunchGPT: A chatGPT assisted framework for scientific machine learning
Scientific Machine Learning (SciML) has advanced recently across many di...
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03/15/2023
ViTO: Vision Transformer-Operator
We combine vision transformers with operator learning to solve diverse i...
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01/04/2023
MessageNet: Message Classification using Natural Language Processing and Meta-data
In this paper we propose a new Deep Learning (DL) approach for message c...
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11/17/2022
SMS: Spiking Marching Scheme for Efficient Long Time Integration of Differential Equations
We propose a Spiking Neural Network (SNN)-based explicit numerical schem...
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10/31/2022
On the Geometry Transferability of the Hybrid Iterative Numerical Solver for Differential Equations
The discovery of fast numerical solvers prompted a clear and rapid shift...
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08/28/2022
A Hybrid Iterative Numerical Transferable Solver (HINTS) for PDEs Based on Deep Operator Network and Relaxation Methods
Iterative solvers of linear systems are a key component for the numerica...
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08/07/2022
A physically-informed Deep-Learning approach for locating sources in a waveguide
Inverse source problems are central to many applications in acoustics, g...
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05/22/2022
A Convolutional Dispersion Relation Preserving Scheme for the Acoustic Wave Equation
We propose an accurate numerical scheme for approximating the solution o...
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05/17/2022
