AIMC Topic: Neural Networks, Computer

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A Time Series Forecasting Approach Based on Nonlinear Spiking Neural Systems.

International journal of neural systems Mar 8, 2022
Nonlinear spiking neural P (NSNP) systems are a recently developed theoretical model, which is abstracted by nonlinear spiking mechanism of biological neurons. NSNP systems have a nonlinear structure and the potential to describe nonlinear dynamic sy...
Neural Networks, Computer Forecasting Time Factors Nonlinear Dynamics Wavelet Analysis
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Compression of Deep Neural Networks based on quantized tensor decomposition to implement on reconfigurable hardware platforms.

Neural networks : the official journal of the International Neural Network Society Mar 8, 2022
Deep Neural Networks (DNNs) have been vastly and successfully employed in various artificial intelligence and machine learning applications (e.g., image processing and natural language processing). As DNNs become deeper and enclose more filters per l...
Neural Networks, Computer Artificial Intelligence Machine Learning Algorithms Data Compression
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Differentiation between subchondral insufficiency fractures and advanced osteoarthritis of the knee using transfer learning and an ensemble of convolutional neural networks.

Injury Mar 8, 2022
PURPOSE: Subchondral insufficiency fractures (SIF) and advanced osteoarthritis (OA) of the knee are usually seen in conjunction with bone marrow lesions (BMLs) and their differentiation may pose a significant diagnostic challenge. We aimed to develop...
Humans Neural Networks, Computer Retrospective Studies Deep Learning ROC Curve Osteoarthritis, Knee Fractures, Stress
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Synchronization and state estimation for discrete-time coupled delayed complex-valued neural networks with random system parameters.

Neural networks : the official journal of the International Neural Network Society Mar 8, 2022
In this paper, an array of discrete-time coupled complex-valued neural networks (CVNNs) with random system parameters and time-varying delays are introduced. The stochastic fluctuations of system parameters, which are characterized by a set of random...
Neural Networks, Computer Computer Simulation Time Factors
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Lifelong 3D object recognition and grasp synthesis using dual memory recurrent self-organization networks.

Neural networks : the official journal of the International Neural Network Society Mar 8, 2022
Humans learn to recognize and manipulate new objects in lifelong settings without forgetting the previously gained knowledge under non-stationary and sequential conditions. In autonomous systems, the agents also need to mitigate similar behaviour to ...
Humans Neural Networks, Computer Machine Learning Learning Hand Strength Visual Perception
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Neural networks in pulsed dipolar spectroscopy: A practical guide.

Journal of magnetic resonance (San Diego, Calif. : 1997) Mar 8, 2022
This is a methodological guide to the use of deep neural networks in the processing of pulsed dipolar spectroscopy (PDS) data encountered in structural biology, organic photovoltaics, photosynthesis research, and other domains featuring long-lived ra...
Neural Networks, Computer Electron Spin Resonance Spectroscopy
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History Dependence in a Chemical Reaction Network Enables Dynamic Switching.

Small (Weinheim an der Bergstrasse, Germany) Mar 8, 2022
This work describes an enzymatic autocatalytic network capable of dynamic switching under out-of-equilibrium conditions. The network, wherein a molecular fuel (trypsinogen) and an inhibitor (soybean trypsin inhibitor) compete for a catalyst (trypsin)...
Neural Networks, Computer Catalysis Trypsin
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AI-Driven Synthetic Route Design Incorporated with Retrosynthesis Knowledge.

Journal of chemical information and modeling Mar 8, 2022
Computer-aided synthesis planning (CASP) aims to assist chemists in performing retrosynthetic analysis for which they utilize their experiments, intuition, and knowledge. Recent breakthroughs in machine learning (ML) techniques, including deep neural...
Humans Neural Networks, Computer Machine Learning Software
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An Interpretable Convolutional Neural Network Framework for Analyzing Molecular Dynamics Trajectories: a Case Study on Functional States for G-Protein-Coupled Receptors.

Journal of chemical information and modeling Mar 8, 2022
Molecular dynamics (MD) simulations have made great contribution to revealing structural and functional mechanisms for many biomolecular systems. However, how to identify functional states and important residues from vast conformation space generated...
Neural Networks, Computer Software Receptors, G-Protein-Coupled Molecular Dynamics Simulation
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Machine Learning May Sometimes Simply Capture Literature Popularity Trends: A Case Study of Heterocyclic Suzuki-Miyaura Coupling.

Journal of the American Chemical Society Mar 8, 2022
Applications of machine learning (ML) to synthetic chemistry rely on the assumption that large numbers of literature-reported examples should enable construction of accurate and predictive models of chemical reactivity. This paper demonstrates that a...
Neural Networks, Computer Machine Learning Algorithms Solvents
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