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hiyenwong/ai_collection수집된 skill 4,114개 중 40개를 표시합니다.
Modeling sequential cognitive states via population-level cortical dynamics using Universal Approximation Theorem to approximate heteroclinic cycles with neural field systems. Activation: heteroclinic cognitive states, sequential brain dynamics,…
원문 언어: 영어
Heteroclinic dynamics with discrete neural-field equations for modeling sequential cognitive states. Uses Universal Approximation Theorem to approximate target heteroclinic dynamics by Amari-type neural-field systems. Activates: heteroclinic cycle, sequential…
원문 언어: 영어
Heterogeneous assume-guarantee contract framework for co-design of layered control architectures. Decomposes safety-liveness specifications across discrete-time planning (MPC) and continuous-time safety layers using vertical refinement, timing compatibility,…
원문 언어: 영어
分布式非凸复合优化的异构随机动量ADMM方法。通过节点自适应步长策略解耦算法稳定性与全局网络属性，实现任意连接拓扑下的鲁棒收敛。适用于分布式机器学习、联邦学习、网络优化。触发词：分布式优化、ADMM、随机优化、非凸优化、动量加速、异构网络、distributed optimization、stochastic ADMM、heterogeneous network。
원문 언어: 중국어
异质突触动力学建模方法论。基于现象学建模框架，整合连接性、突触传输、突触可塑性和突触异质性四个关键维度。适用于大规模脑网络模拟、突触模型实现、计算神经科学研究。触发词：突触动力学、异质性建模、突触可塑性、突触传输、计算神经科学、synaptic dynamics, heterogeneous synapses, computational neuroscience。
원문 언어: 중국어
Heterophily as a generative mechanism for self-organized synergistic interdependencies in adaptive networks. Explains how heterophily induces higher-order dependencies while weakening pairwise dependencies, enabling robust collective behavior. Trigger words:…
원문 언어: 영어
Framework for rapidly inferring Hodgkin-Huxley (HH) biophysical parameters from extracellular multi-electrode array (MEA) measurements using differentiable biophysical simulation and simulation-based inference. Enables precise neurostimulation prediction…
원문 언어: 영어
Hidden progress during overtraining in sensory cortex networks — discovering that overtrained neural networks continue learning useful representations even after apparent performance plateau, with implications for neuroscience and deep learning theory.…
원문 언어: 영어
Hierarchical organization of critical brain dynamics. Studies how criticality signatures vary along anatomical hierarchy in brain systems using phenomenological renormalization group approaches on large-scale neuronal spiking data.
원문 언어: 영어
Parallelized Hierarchical Connectome (PHC) framework for spatiotemporal recurrent spiking neural networks. Upgrades State-Space Models (SSMs) into spatiotemporal networks with biological constraints including Dale's Law, short-term plasticity, and…
원문 언어: 영어
Parallelized Hierarchical Connectome (PHC) framework that upgrades temporal State-Space Models into spatiotemporal recurrent networks for brain connectivity modeling.. Activation: hierarchical connectome, state-space models, spatiotemporal.
원문 언어: 영어
Hierarchical control design via approximate simulation relations (ε-gAAS). Enables abstraction-based controller synthesis for continuous-time nonlinear systems with formal error bounds and control refinement guarantees. Use when: (1) designing controllers for…
원문 언어: 영어
Hierarchical control synthesis for continuous-time systems using epsilon-general Approximate Alternating Simulation (epsilon-gAAS) relations. Enables formal controller design with coarser abstractions while maintaining correctness guarantees. Use when: (1)…
원문 언어: 영어
Hierarchical organization of critical brain dynamics. Analysis of how brain structure hierarchies interact with criticality hypothesis. Activation: hierarchical brain, critical dynamics, connectome hierarchy, brain criticality.
원문 언어: 다국어 혼합
Higher-order brain network analysis using topological signal processing. Captures circulatory and multi-node interactions beyond pairwise graph models.. Activation: higher-order networks, topological signal processing, brain connectomics.
원문 언어: 영어
Methodology for extracting high-order functional brain network structures beyond pairwise connections under global constraints. Addresses theoretical limitations of pairwise FBN modeling. Activation: higher-order brain networks, beyond pairwise, global…
원문 언어: 영어
Extracting interpretable higher-order topological features across multiple scales for Alzheimer's Disease classification using persistent homology. Captures connected components, cycles, and cavities from fMRI brain networks. Activation: higher-order…
원문 언어: 영어
Biologically detailed extension of Hopfield/Marr auto-associative memory model for CA3 hippocampus. Implements ten populations (two asymmetric pyramidal subtypes, eight GABAergic interneurons) to study multi-attractor dynamics and stability effects in memory…
원문 언어: 영어
Brain-inspired hierarchical world model using hippocampal-entorhinal (HPC-MEC) circuit for structure abstraction and generalization. Inverse model for structural extraction, HPC-MEC coupling for dissociating relational structures from episodic scenes. Based…
원문 언어: 영어
HoloBrain and HoloGraph framework: modeling brain rhythms through coupled oscillatory synchronization and applying this principle to graph neural networks. Addresses GNN over-smoothing and enables reasoning on graphs through oscillatory dynamics.
원문 언어: 영어
Homology-based morphometry methods for analyzing brain atrophy using topological data analysis. Activation triggers: homology morphometry, brain atrophy, topological neuroimaging, persistent homology brain, TDA neuroimaging
원문 언어: 영어
Homology-based Morphometry (HBM) methodology for analyzing brain atrophy using persistent homology. Two complementary pipelines for quantifying multiscale geometric features of structural T1-weighted MRI scans: Pipeline 1 for regional thinning via Euclidean…
원문 언어: 영어
Hormone-inspired Emotion Layer for Transformer language models (HELT / HormoneT5). Biologically-inspired architecture augmenting transformers with a Hormone Emotion Block simulating the endocrine system's role in emotional processing. Six continuous…
원문 언어: 영어
Hot-starting methodology for quantum portfolio optimization using continuous relaxation to construct compact Hilbert space, reducing qubit requirements for QUBO formulations. Based on arXiv:2510.11153v1.
원문 언어: 영어
Hot-starting methodology for quantum portfolio optimization — restricting search space to discrete solutions near the continuous optimum by constructing a compact Hilbert space, reducing qubit requirements.
원문 언어: 영어
Chain-of-thought monitoring methodology for detecting misalignment in coding agents. GPT-5.4 Thinking monitors 99.9% of internal coding agent traffic. Defense-in-depth approach with layered controls. Use when implementing agent safety systems or building…
원문 언어: 영어
Hybrid Quantum-Classical Neural Network (HQNN) methodology for medical image classification, specifically blood cell classification. Combines pre-trained classical backbone (ResNet-50) with variational quantum circuit for enhanced feature representation. Use…
원문 언어: 영어
Hybrid Quantum Neural Network (HQNN) architecture for breast cancer thermographic classification. Integrates parameterized quantum circuits with multi-head attention and classical CNN layers for enhanced medical thermal pattern recognition.
원문 언어: 영어
Expressibility-trainability trade-off analysis and multi-objective NAS framework for Hybrid Quantum Neural Networks (HQNNs) — reveals how classical components reshape quantum optimization landscapes and decouple trainability from PQC expressibility.
원문 언어: 영어
Higher-Order Unconstrained Binary Optimization (HUBO) methodology for quantum optimization workflows. Compact binary encoding reduces qubit requirements vs QUBO but increases circuit depth via higher-order interaction terms. Use when formulating industrial…
원문 언어: 영어
Behavioral benchmark and object-centricity analysis for self-supervised vision transformers. Uses two-dot same/different judgment task with 1020+ trials to measure human object grouping, and proposes Gram matrix alignment as a mechanism for improving…
원문 언어: 영어
Hybrid ANN-SNN pipeline with local plasticity: couples pretrained ANN encoders with spiking classifiers using biologically-inspired local learning rules, bypassing end-to-backprop. Use when building energy-efficient spiking neural networks from pretrained…
원문 언어: 영어
Learning Hybrid Biophysical Neuron Models with Neural ODEs — combining mechanistic biophysical models with machine learning for accurate and efficient neuron dynamics modeling
원문 언어: 영어
Hybrid biophysical neuron modeling methodology combining conductance-based models with neural ODEs. Captures unknown ion channel kinetics while preserving mechanistic interpretability. Enables single-compartment reduction of multi-compartment models.
원문 언어: 영어
Multi-dimensional mental health assessment using hybrid intelligent frameworks combining clinically validated screening tools, cognitive evaluation, and personality profiling with AI-driven decision support.
원문 언어: 영어
Hybrid certificate methodology combining ECC with Post-Quantum Cryptography (PQC) for vehicular communication security. Covers SCMS pseudonym schemes, BKE compatibility, NIST-standardized PQC algorithms, and performance evaluation of RSA/ECC/PQC for vehicular…
원문 언어: 영어
Hybrid classical-quantum diagnostic framework using QCNNs for multi-class medical image classification
원문 언어: 영어
Design and evaluate hybrid quantum-classical machine learning pipelines. Covers NISQ-era variational quantum algorithms (VQAs), noise-aware pipeline design, correlation-guided quantum circuit construction, and classical-quantum benchmarking frameworks. Use…
원문 언어: 영어
Design dataflow-based hybrid quantum-classical computing architectures. Combine remote quantum computers with cloud/distributed systems. Activation: hybrid quantum classical, quantum classical hybrid, 混合量子经典, dataflow quantum, quantum cloud computing.
원문 언어: 영어
Hybrid quantum-classical physics-informed neural network (HQPINN) methodology for solving nonlinear PDEs. Integrates classical NN backbone with parameterized quantum circuits (PQC) to enrich solution representation for problems with sharp gradients, stiff…
원문 언어: 영어