Search Results - Phase coherence graph autoencoder

Self-organizing dynamic research based on phase coherence graph autoencoders: Analysis of brain metastable states across the lifespan

Authors: Hao Guo Yu-Xuan Liu Yao Li et al.

Source: NeuroImage, Vol 310, Iss , Pp 121119- (2025)

Subject Terms: Resting state fMRI, Entire lifespan, Phase coherence graph autoencoder, Metastable state, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S1053811925001211; https://doaj.org/toc/1095-9572

Access URL: https://doaj.org/article/3b4f1e561b7542fd9bad91c55cc1d708

Quantoscope: Quantum Reconstruction Revolution for Time-Symmetric Imaging of Quantum Memory, Gluons, and Vacuum Fields

Authors: JALALI, SEYED RASOUL

Subject Terms: Quantoscope, Quantum Imaging, Quantum Reconstruction, Time-Symmetric Imaging, Quantum Memory, Gluons, Vacuum Fields, ψ–Hamzah Equation, Informational Geometry, Sub-Planck Imaging, Retrocausality, Fractal Lenses, Memory Wavefunction, ψ–Vision Algorithm, Quantum Neural Networks, Nano-Quantum Accelerator, HNAQ, Nonlinear Optics, Quantum Resonance, Informational Vacuum, Quantum Silence, Consciousness Imaging, Quantum Awareness, Informational Reconstruction, ψ–Memory, Sub-Planckian Phenomena, Quantum Chromodynamics, QCD Imaging, Quark Observation, SU(3) Color Structures, Virtual Particles, Quantum Noise Cancellation, Decoherence Mitigation, Informational Spectrum, ψ–Color Vector, Temporal Feedback, Informational Interferometry, ψ–Optical Matrix, ψ–Resonance Spectrum, Quantum Information Theory, Zero-Noise Communication, Quantum Coherence, Quantum Entanglement, Informational Phase, ψ–Encoding, Temporal Memory Index, Fractal Derivatives, Informational Lenses, Memory-Based Imaging, Cognitive Quantum Science, Quantum Biology, Quantum Computing, Quantum Sensors, ψ–Fractal Lens, Informational Feedback, Retrocausal Models, Non-Abelian Gauge Theory, Vacuum Oscillations, ψ–Vacuum Field, ψ–Resonance, Informational Field Theory, Quantum Awareness Models, Quantum Silence Spectrum, Informational Signal, Quantum Mind, Cognitive Resonance, Brain–Quantum Interface, ψ–Brain Interface, Quantum Neuroimaging, Quantum Prosthetics, Informational Nanomedicine, Quantum Diagnosis, Quantum Nano-Machines, ψ–Medical Imaging, Quantum Therapy, DNA Resonance, Protein Quantum Memory, Photosynthesis Efficiency, Cellular Quantum Coherence, Informational Biology, Quantum Mind Models, Cognitive Encoding, Informational Awareness, Conscious Silence, Awareness Fields, Quantum Philosophy, Epistemological Imaging, Informational Epistemology, Consciousness Studies, Retrocausal Cognition, Informational Awareness Fields, Temporal Nonlocality, Quantum Cognition, Informational Psychology, ψ–Mind Model, Informational Consciousness, Quantum Decision-Making, Informational Cognition, Future Feedback, Quantum Human Sciences, Informational Sociology, Quantum Anthropology, Informational Archaeology, Informational Epistemics, Dark Energy Imaging, Cosmic Silence, Informational Cosmology, Quantum Vacuum Analysis, Casimir Hotspots, Vacuum Condensation, Informational Dark Matter, Astrophysical ψ–Imaging, Cosmic Resonance, Interstellar Vacuum Fluctuations, Extraterrestrial Signal Analysis, ETI Scan, ψ–Cosmic Spectrum, Quantum Universe Imaging, ψ–Cosmology, Informational Astronomy, Particle Memory, Informational Quark–Gluon Plasma, Informational Nucleon Structure, ψ–Strong Force Imaging, Informational Gluon Fields, QCD Resonance, Informational Color Vectors, ψ–Color Mapping, Informational Quantum Chromodynamics, ψ–Topological Phases, Quantum Topological Imaging, Informational SU(3), ψ–QCD Feedback, Informational Energy Gaps, Informational Phase Nodes, ψ–Phase Analysis, ψ–Energy Density, Informational Spectrum Analysis, Informational Coherence, Informational Decoherence, Informational Noise Filtering, ψ–Decoherence Mitigation, Informational Qubit Stability, Informational Entanglement, ψ–Qubit Imaging, Informational Quantum Computing, ψ–Qubit Memory, ψ–Quantum Machine Learning, Quantum Perception, ψ–Perceptual Awareness, Quantum Cognitive AI, ψ–Quantum Neural Network, ψ–Autoencoder, ψ–Memory Graphs, Informational Memory Maps, ψ–Graph Processing, ψ–Quantum GPU, ψ–Quantum Hardware, ψ–Nanoelectronics, ψ–Metamaterial Lenses, Informational Nanotechnology, ψ–Quantum Optoelectronics, Informational Feedback Systems, Informational Quantum Photonics, ψ–HyperQuantum Processor, ψ–QNN Imaging, ψ–Quantum Processor, Quantum Photonic Imaging, Informational Holography, ψ–HoloProjector, ψ–7D Projections, Informational Spin Imaging, ψ–Temporal Imaging, Informational Time-Symmetric Operators, ψ–Bidirectional Wave Equations, ψ–Feedback Kernels, Retarded Kernels, Advanced Kernels, Informational Retrodynamics, ψ–Temporal Symmetry, ψ–Vacuum Information, Informational Ground State, ψ₀(x,t), Informational Oscillations, ψ–Fourier Transform, ψ–Wavelet Transform, ψ–Hermitian Transform, ψ–Fractional Transform, Informational Phase Mapping, Informational Frequency Filtering, ψ–Delay Embedding, ψ–Deconvolution Engine, ψ–Reconstruction Algorithm, ψ–AutoCorrelated Filters, Informational Gradient Mapping, ψ–Informational Interference, Informational Feedback Mapping, ψ–Vacuum Resonance, Informational Color Filters, ψ–Color Amplification, ψ–Quantum Wavelet Transform, Informational Phase Coherence, ψ–Decoherence Delay, Informational SU(3) Mapping, ψ–Memory Fidelity, Informational Fidelity Metrics, Informational SSIM, Informational PSNR, ψ–Error Management, ψ–Noise Spectrum, Informational Stability Analysis, ψ–Stability Dynamics, Informational Nonlocality, ψ–Feedback Resonance, ψ–Fractal Feedback, Informational Recursion, ψ–Recursive Functions, Informational Phase Diffusion, ψ–NonGaussian Memory, ψ–Fractional Diffusion, ψ–Nonlinear Memory, Informational Nonlinearity, ψ–Tensorial Functions, ψ–Optical Matrix, ψ–Resonance Domain, ψ–Resonant Peaks, Informational Imaging Spectrum, Informational Tensor Analysis, ψ–Graphical Reconstruction, ψ–Heatmaps, ψ–Quantum Spectrum Analysis, ψ–Spectral Tensor, ψ–Resonant Mapping, Informational Phase–Time Mapping, ψ–Fractal Information Spectrum, ψ–Informational Holography, Informational Retro-Imaging, ψ–Feedback Loops, Informational Chronodynamics, ψ–Temporal Coherence, ψ–Vacuum Noise Resonance, ψ–Informational Silence, Quantum Silence Imaging, Informational Zero-Noise, ψ–Signal-to-Silence Mapping, Informational Signal Extraction, ψ–Silence Coherence, ψ–Silent Awareness, ψ–Silent Intelligence, Informational Vacuum Intelligence, ψ–Quantum Silence Spectrum, ψ–Vacuum Intelligence, ψ–Epistemic Interface, ψ–Ontological Imaging, Informational Ontology, ψ–Epistemology, ψ–Technological Framework, Informational Cognitive Interface, ψ–Cognitive Lens, ψ–Cognitive Feedback, ψ–Cognitive Awareness, ψ–Artificial Consciousness, ψ–Neuromorphic AI, ψ–Quantum AI, ψ–Cognitive Quantum Networks, ψ–Awareness Encoding, ψ–Conscious Encoding, ψ–Resonant Cognition, ψ–Philosophy of Mind, ψ–Informational Awareness Studies, ψ–Mind–Machine Interface, ψ–Informational Epistemics, ψ–Hamzah Microscope, ψ–Hamzah Imaging, ψ–Hamzah Lens, ψ–Hamzah Neural Imaging, ψ–Hamzah Neural Networks, ψ–Hamzah QNN, ψ–Hamzah Imaging Systems, ψ–Hamzah Cognitive Field, ψ–Hamzah Resonance, ψ–Hamzah Retrocausal Models, ψ–Hamzah Informational Awareness, ψ–Hamzah Quantum Feedback, ψ–Hamzah Physics, ψ–Hamzah Medicine, ψ–Hamzah Biology, ψ–Hamzah AI, ψ–Hamzah Cognitive Science, ψ–Hamzah Quantum Information, ψ–Hamzah Quantum Cosmology, ψ–Hamzah Quantum Mind, ψ–Hamzah Quantum Cognition, ψ–Hamzah Quantum Medicine, ψ–Hamzah Quantum Biology, ψ–Hamzah Quantum Computing, ψ–Hamzah Quantum Neuroscience, ψ–Hamzah Quantum Philosophy, ψ–Hamzah Universal Applications

Graph-informed convolutional autoencoder to classify brain responses during sleep

Authors: Sahar Zakeri Somayeh Makouei Sebelan Danishvar

Source: Front Neurosci
Frontiers in Neuroscience, Vol 19 (2025)

Subject Terms: graphical representation, auditory stimuli, functional connectivity, convolutional neural network, Neurosciences. Biological psychiatry. Neuropsychiatry, EEG, sleep, RC321-571, Neuroscience

Access URL: https://pubmed.ncbi.nlm.nih.gov/40356705
https://doaj.org/article/a03711a5ed214646aa5c2d62ac7f7aca

SpaCross deciphers spatial structures and corrects batch effects in multi-slice spatially resolved transcriptomics.

Authors: Fang, Donghai Min, Wenwen

Source: Communications Biology; 9/30/2025, Vol. 8 Issue 1, p1-19, 19p

Subject Terms: GENE expression, TRANSCRIPTOMES, PATTERN recognition systems, GRAPH neural networks, MORPHOLOGY

Generating 3D House Wireframes with Semantics

Authors: Ma, Xueqi Liu, Yilin Zhou, Wenjun et al.

Index Terms: Computer Science - Computer Vision and Pattern Recognition, Computer Science - Graphics, text

URL: http://arxiv.org/abs/2407.12267

Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning.

Authors: Liu, Yixin Li, Zhao Pan, Shirui et al.

Source: IEEE Transactions on Neural Networks & Learning Systems; Jun2022, Vol. 33 Issue 6, p2378-2392, 15p

Subject Terms: ANOMALY detection (Computer security), DEEP learning, INFORMATION networks, SUPERVISED learning, ARTIFICIAL neural networks

Connectogram-COH: A Coherence-Based Time-Graph Representation for EEG-Based Alzheimer's Disease Detection.

Authors: Aljanabi, Ehssan Türker, İlker

Source: Diagnostics (2075-4418); Jun2025, Vol. 15 Issue 11, p1441, 22p

Subject Terms: ALZHEIMER'S disease, REPRESENTATIONS of graphs, DEEP learning, COHERENCE (Physics), TIME series analysis

Application of Graph-Theoretic Methods Using ERP Components and Wavelet Coherence on Emotional and Cognitive EEG Data.

Authors: Deniz, Sencer Melih Ademoglu, Ahmet Duru, Adil Deniz et al.

Source: Brain Sciences (2076-3425); Jul2025, Vol. 15 Issue 7, p714, 24p

Subject Terms: EMOTIONS, COGNITION, WAVELETS (Mathematics), ELECTROENCEPHALOGRAPHY, SUPERVISED learning, EVOKED potentials (Electrophysiology), ELECTROPHYSIOLOGY, GRAPH theory

An effective video captioning based on language description using a novel Graylag Deep Kookaburra Reinforcement Learning.

Authors: Shankar, M. Gowri Surendran, D.

Source: EURASIP Journal on Image & Video Processing; 1/9/2025, Vol. 2025 Issue 1, p1-27, 27p

Subject Terms: DEEP reinforcement learning, REINFORCEMENT learning, INFORMATION storage & retrieval systems, SPARSE graphs, ARTIFICIAL intelligence

Scattering Characteristic Analysis and Ship Detection Using Polarimetric Autocorrelation Matrix.

Authors: Li, Yi Yu, Hui Liu, Genwang et al.

Source: Sensing & Imaging; 10/18/2025, Vol. 26 Issue 1, p1-15, 15p

The MLDAR Model: Machine Learning-Based Denoising of Structural Response Signals Generated by Ambient Vibration.

Authors: Damikoukas, Spyros Lagaros, Nikos D.

Source: Computation; Feb2024, Vol. 12 Issue 2, p31, 25p

Subject Terms: STRUCTURAL health monitoring, ELECTRONIC noise, IMAGE denoising, SIGNAL-to-noise ratio, EIGENFREQUENCIES, MACHINE learning, DEEP learning, ELECTRIC oscillators

DHCLHAM: microbe-drug interaction prediction based on dual-hypergraph contrastive learning framework with hierarchical attention mechanism.

Authors: Hu, Hailong Nie, Cong

Source: Frontiers in Microbiology; 2025, p1-21, 21p

Subject Terms: HYPERGRAPHS, COMPUTATIONAL biology, MACHINE learning, QUANTITATIVE research, INDIVIDUALIZED medicine

Artificial Intelligence in Small-Molecule Drug Discovery: A Critical Review of Methods, Applications, and Real-World Outcomes.

Authors: Niazi, Sarfaraz K.

Source: Pharmaceuticals (14248247); Sep2025, Vol. 18 Issue 9, p1271, 28p

Subject Terms: ARTIFICIAL intelligence, DRUG development, BIOINFORMATICS, DRUG repositioning, MOLECULAR pharmacology, INFORMATION technology

Recent advances in deep learning for protein-protein interaction: a review.

Authors: Cui, Jiafu Yang, Siqi Yi, Litai et al.

Source: BioData Mining; 6/16/2025, Vol. 18 Issue 1, p1-23, 23p

Subject Terms: ARTIFICIAL neural networks, ARTIFICIAL intelligence, MACHINE learning, COMPUTATIONAL biology, CONVOLUTIONAL neural networks, DEEP learning

A deep generative approach to cancer prognosis: MMD-VAE for multi-omics data fusion.

Authors: Hassan, Asmaa M. Naeem, Safaa M. Eldosoky, Mohamed A. A. et al.

Source: Network Modeling & Analysis in Health Informatics & Bioinformatics; 8/31/2025, Vol. 14 Issue 1, p1-22, 22p

Optical strategies for in vivo retinal ganglion cell imaging.

Authors: Chen, Justin Fang, Raymond Liu, Xiaorong et al.

Source: Med-X; 11/17/2025, Vol. 3 Issue 1, p1-21, 21p

An automated extraction of spectral-temporal and spatial-temporal features of EEG for emotion detection.

Authors: Islam, Monira Lee, Tan

Source: Brain Informatics; 8/2/2025, Vol. 12 Issue 1, p1-19, 19p

Subject Terms: EMOTION recognition, ELECTROENCEPHALOGRAPHY, MULTIVARIATE analysis, SIGNAL processing, SPECTRUM analysis, DEEP learning

Robust virtual staining of landmark organelles with Cytoland.

Authors: Liu, Ziwen Hirata-Miyasaki, Eduardo Pradeep, Soorya et al.

Source: Nature Machine Intelligence; Jun2025, Vol. 7 Issue 6, p901-915, 15p

From Innovation to Application: Can Emerging Imaging Techniques Transform Breast Cancer Diagnosis?

Authors: Hsu, Honda Lee, Kun-Hua Karmakar, Riya et al.

Source: Diagnostics (2075-4418); Nov2025, Vol. 17 Issue 21, p2718, 48p

Subject Terms: BREAST cancer, DIAGNOSTIC imaging, MACHINE learning, DEEP learning, CLINICAL trials

From pixels to cell types: a comprehensive review of computational methods for spatial transcriptomics deconvolution.

Authors: Saqib, Jahanzeb Kim, Junil

Source: Genomics & Informatics; 10/31/2025, Vol. 23 Issue 1, p1-22, 22p