AIMC Topic: Physics

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Hebbian dreaming for small datasets.

Neural networks : the official journal of the International Neural Network Society Feb 12, 2024
The dreaming Hopfield model constitutes a generalization of the Hebbian paradigm for neural networks, that is able to perform on-line learning when "awake" and also to account for off-line "sleeping" mechanisms. The latter have been shown to enhance ...
Neural Networks, Computer Machine Learning Algorithms Generalization, Psychological Physics
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Lie-Poisson Neural Networks (LPNets): Data-based computing of Hamiltonian systems with symmetries.

Neural networks : the official journal of the International Neural Network Society Feb 3, 2024
An accurate data-based prediction of the long-term evolution of Hamiltonian systems requires a network that preserves the appropriate structure under each time step. Every Hamiltonian system contains two essential ingredients: the Poisson bracket and...
Neural Networks, Computer Physics Physical Phenomena
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Using slisemap to interpret physical data.

PloS one Jan 25, 2024
Manifold visualisation techniques are commonly used to visualise high-dimensional datasets in physical sciences. In this paper, we apply a recently introduced manifold visualisation method, slisemap, on datasets from physics and chemistry. slisemap c...
Artificial Intelligence Machine Learning Physical Examination Physics Relaxation Therapy
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Physics-informed kernel function neural networks for solving partial differential equations.

Neural networks : the official journal of the International Neural Network Society Jan 2, 2024
This paper proposes an improved version of physics-informed neural networks (PINNs), the physics-informed kernel function neural networks (PIKFNNs), to solve various linear and some specific nonlinear partial differential equations (PDEs). It can als...
Neural Networks, Computer Diethylstilbestrol Physics
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Physics-guided neural network for predicting asphalt mixture rutting with balanced accuracy, stability and rationality.

Neural networks : the official journal of the International Neural Network Society Dec 27, 2023
The prediction of rutting performance of asphalt materials poses a significant challenge due to the intricate relationships between the rutting performance and its influencing factors. Machine learning models have gained popularity to address this ch...
Neural Networks, Computer Algorithms Hydrocarbons Physics
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Insights into Materials, Physics, and Applications in Flexible and Wearable Acoustic Sensing Technology.

Advanced materials (Deerfield Beach, Fla.) Dec 10, 2023
Sound plays a crucial role in the perception of the world. It allows to communicate, learn, and detect potential dangers, diagnose diseases, and much more. However, traditional acoustic sensors are limited in their form factors, being rigid and cumbe...
Humans Technology Wearable Electronic Devices Robotics Acoustics Physics
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Predicting intratumoral fluid pressure and liposome accumulation using physics informed deep learning.

Scientific reports Nov 23, 2023
Liposome-based anticancer agents take advantage of the increased vascular permeability and transvascular pressure gradients for selective accumulation in tumors, a phenomenon known as the enhanced permeability and retention(EPR) effect. The EPR effec...
Animals Neoplasms Deep Learning Mice Extracellular Fluid Liposomes Physics
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Leveraging spatial residual attention and temporal Markov networks for video action understanding.

Neural networks : the official journal of the International Neural Network Society Oct 31, 2023
The effective use of temporal relationships while extracting fertile spatial features is the key to video action understanding. Video action understanding is a challenging visual task because it generally necessitates not only the features of individ...
Neural Networks, Computer Learning Physics
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Physics-informed neural network for fast prediction of temperature distributions in cancerous breasts as a potential efficient portable AI-based diagnostic tool.

Computer methods and programs in biomedicine Sep 29, 2023
This work presents the development of a novel Physics-Informed Neural Network (PINN) method for fast forward simulation of heat transfer through cancerous breast models. The proposed PINN method combines deep learning and physical principles to predi...
Humans Neural Networks, Computer Artificial Intelligence Female Temperature Breast Neoplasms Physics
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Applications and Advances in Machine Learning Force Fields.

Journal of chemical information and modeling Sep 26, 2023
Force fields (FFs) form the basis of molecular simulations and have significant implications in diverse fields such as materials science, chemistry, physics, and biology. A suitable FF is required to accurately describe system properties. However, an...
Machine Learning Physics
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