AIMC Topic: Neural Networks, Computer

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Quantum weighted long short-term memory neural network and its application in state degradation trend prediction of rotating machinery.

Neural networks : the official journal of the International Neural Network Society
Classical long short-term memory neural network (LSTMNN) generally faces the challenges of poor generalization property and low training efficiency in state degradation trend prediction of rotating machinery. In this paper, a novel quantum neural net...

Evaluation of the computational capabilities of a memristive random network (MN) under the context of reservoir computing.

Neural networks : the official journal of the International Neural Network Society
This work presents the simulation results of a novel recurrent, memristive neuromorphic architecture, the MN and explores its computational capabilities in the performance of a temporal pattern recognition task by considering the principles of the re...

Deep reinforcement learning for de novo drug design.

Science advances
We have devised and implemented a novel computational strategy for de novo design of molecules with desired properties termed ReLeaSE (Reinforcement Learning for Structural Evolution). On the basis of deep and reinforcement learning (RL) approaches, ...

Optimization of multiplex quantitative polymerase chain reaction based on response surface methodology and an artificial neural network-genetic algorithm approach.

PloS one
Multiplex quantitative polymerase chain reaction (qPCR) has found an increasing range of applications. The construction of a reliable and dynamic mathematical model for multiplex qPCR that analyzes the effects of interactions between variables is the...

Evaluation of multiple linear, neural network and penalised regression models for prediction of rice yield based on weather parameters for west coast of India.

International journal of biometeorology
Rice is generally grown under completely flooded condition and providing food for more than half of the world's population. Any changes in weather parameters might affect the rice productivity thereby impacting the food security of burgeoning populat...

Can China fulfill its commitment to reducing carbon dioxide emissions in the Paris Agreement? Analysis based on a back-propagation neural network.

Environmental science and pollution research international
Due to the increasingly severe situation regarding adaptation to climate change, global attention has focused on whether China can fulfill its commitment to the Paris Agreement as the largest producer of carbon dioxide (CO) emissions. In this study, ...

Shared spatiotemporal category representations in biological and artificial deep neural networks.

PLoS computational biology
Visual scene category representations emerge very rapidly, yet the computational transformations that enable such invariant categorizations remain elusive. Deep convolutional neural networks (CNNs) perform visual categorization at near human-level ac...

Deep Generative Adversarial Neural Networks for Compressive Sensing MRI.

IEEE transactions on medical imaging
Undersampled magnetic resonance image (MRI) reconstruction is typically an ill-posed linear inverse task. The time and resource intensive computations require tradeoffs between accuracy and speed. In addition, state-of-the-art compressed sensing (CS)...

Learning to Segment Object Candidates via Recursive Neural Networks.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
To avoid the exhaustive search over locations and scales, current state-of-the-art object detection systems usually involve a crucial component generating a batch of candidate object proposals from images. In this paper, we present a simple yet effec...