AIMC Topic: Entropy

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Graph Spring Network and Informative Anchor Selection for session-based recommendation.

Neural networks : the official journal of the International Neural Network Society Dec 8, 2022
Session-based recommendation (SBR) aims at predicting the next item for an ongoing anonymous session. The major challenge of SBR is how to capture richer relations in between items and learn ID-based item embeddings to capture such relations. Recent ...
Neural Networks, Computer Entropy
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A novel hybrid optimization enabled robust CNN algorithm for an IoT network intrusion detection approach.

PloS one Dec 1, 2022
Due to the huge number of connected Internet of Things (IoT) devices within a network, denial of service and flooding attacks on networks are on the rise. IoT devices are disrupted and denied service because of these attacks. In this study, we propos...
Animals Entropy Heuristics Algorithms Cetacea Neural Networks, Computer Computer Simulation
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Understanding Neural Networks and Individual Neuron Importance via Information-Ordered Cumulative Ablation.

IEEE transactions on neural networks and learning systems Nov 30, 2022
In this work, we investigate the use of three information-theoretic quantities-entropy, mutual information with the class variable, and a class selectivity measure based on Kullback-Leibler (KL) divergence-to understand and study the behavior of alre...
Information Theory Neural Networks, Computer Entropy Neurons
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Learned Gradient Compression for Distributed Deep Learning.

IEEE transactions on neural networks and learning systems Nov 30, 2022
Training deep neural networks on large datasets containing high-dimensional data requires a large amount of computation. A solution to this problem is data-parallel distributed training, where a model is replicated into several computational nodes th...
Neural Networks, Computer Deep Learning Entropy Data Compression
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Combination of explainable machine learning and conceptual density functional theory: applications for the study of key solvation mechanisms.

Physical chemistry chemical physics : PCCP Nov 30, 2022
We present explainable machine learning approaches for the accurate prediction and understanding of solvation free energies, enthalpies, and entropies for different salts in various protic and aprotic solvents. As key input features, we use fundament...
Salts Entropy Solvents Electronics Machine Learning
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Segmentation with mixed supervision: Confidence maximization helps knowledge distillation.

Medical image analysis Nov 7, 2022
Despite achieving promising results in a breadth of medical image segmentation tasks, deep neural networks (DNNs) require large training datasets with pixel-wise annotations. Obtaining these curated datasets is a cumbersome process which limits the a...
Neural Networks, Computer Entropy Semantics Humans
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Multimodal medical image fusion algorithm based on pulse coupled neural networks and nonsubsampled contourlet transform.

Medical & biological engineering & computing Nov 7, 2022
Combining two medical images from different modalities is more helpful for using the resulting image in the healthcare field. Medical image fusion means combining two or more images coming from multiple sensors. This technology obtains an output imag...
Humans Algorithms Image Processing, Computer-Assisted Neural Networks, Computer Signal-To-Noise Ratio Benchmarking Entropy
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Neurodynamics-driven holistic approaches to semi-supervised feature selection.

Neural networks : the official journal of the International Neural Network Society Nov 3, 2022
Feature selection is a crucial part of machine learning and pattern recognition, which aims at selecting a subset of informative features from the original dataset. Because of label information, supervised feature selection performs better than unsup...
Entropy Supervised Machine Learning Machine Learning Neural Networks, Computer Algorithms
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KDE-GAN: A multimodal medical image-fusion model based on knowledge distillation and explainable AI modules.

Computers in biology and medicine Nov 3, 2022
BACKGROUND: As medical images contain sensitive patient information, finding a publicly accessible dataset with patient permission is challenging. Furthermore, few large-scale datasets suitable for training image-fusion models are available. To addre...
Entropy Benchmarking Humans Image Processing, Computer-Assisted Artificial Intelligence
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Identifying autism spectrum disorder in resting-state fNIRS signals based on multiscale entropy and a two-branch deep learning network.

Journal of neuroscience methods Oct 28, 2022
BACKGROUND: The demand for early and precise identification of autism spectrum disorder (ASD) presented a challenge to the prediction of ASD with a non-invasive neuroimaging method.
Entropy Child Humans Autism Spectrum Disorder Spectroscopy, Near-Infrared Brain Deep Learning
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