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Claude Skills by hiyenwong
github.com/hiyenwong9,934 skills5 installs19,223 views
- Hybrid Quantum Financial SecurityEnd-to-end hybrid quantum-classical financial security pipeline integrating VQC forecasting, QUBO annealing, and post-quantum cryptographic signing. Unifies prediction and optimization for financial risk systems under real market constraints. Use when: hybrid quantum finance, VQC forecasting, QUBO portfolio optimization, post-quantum cryptography in finance, end-to-end quantum financial pipelines, financial risk management.Votes: 0GitHub stars: 3
- Hybrid Quantum Medical DiagnosisDesign and evaluate hybrid quantum-classical machine learning pipelines for medical image classification and diagnosis. Covers HQNN, HQCNN, CV-QNN architectures, federated learning with tensor-network frontends, and quantum-enhanced feature extraction for healthcare applications. Use when: (1) building quantum-enhanced medical diagnosis systems, (2) designing hybrid quantum-classical ML pipelines for healthcare, (3) evaluating QML for medical imaging, (4) federated medical learning with quant...Votes: 0GitHub stars: 3
- Hybrid Quantum Medical ImagingHybrid quantum-classical neural network methodology for medical image classification, particularly thermographic breast cancer detection. Integrates quantum neural network layers with classical CNN backbones to enhance pattern recognition in complex medical imaging data. Use when: (1) hybrid quantum-classical architectures for medical diagnosis, (2) quantum-enhanced image classification in healthcare, (3) thermographic/thermal image analysis with quantum methods, (4) quanvolutional networks f...Votes: 0GitHub stars: 3
- Hybrid Tensor Network QmlHybrid tensor network architecture for quantum machine learning using post-selection as a trainable hyperparameter. Interpolates between classical and quantum tensor network edge cases by controlling quantum constraint enforcement via post-selection allocation. Use when designing hybrid quantum-classical ML models, tensor network quantum ML, or optimizing quantum resource allocation with limited post-selection budget. Activation: hybrid tensor network, quantum-classical interpolation, post-se...Votes: 0GitHub stars: 3
- Hybrid Tensor Network Time EvolutionHybrid tensor network time evolution algorithm — parallelizable framework for simulating quantum dynamics using tensor network factorization. Use when simulating quantum many-body dynamics, implementing parallelizable time evolution on tensor networks, studying quantum circuit dynamics, or building scalable quantum simulation algorithms with tensor network methods.Votes: 0GitHub stars: 3
- Hydrogel Neural Interface CoassemblyIn situ self-adaptive hydrogel coating for seamless neural interfaces via okra mucilage polysaccharide and α-helical peptide amphiphile co-assembly. Addresses mechanical mismatch and chronic neuroinflammation in neural electrodes. Exogenous filler-free design with intrinsic conductivity and mechanical flexibility. Activation: neural interface, hydrogel coating, neural electrode, brain implant, neuroinflammation, okra mucilage, peptide amphiphile, co-assembly.Votes: 0GitHub stars: 3
- Hyfu Had Quantum FuzzyHyFuHAD: Hybrid Quantum-Fuzzy Hyperspectral Anomaly Detection methodology. Combines Einstein fuzzy computing for classical inference with lightweight quantum defuzzifier for final detection. Uses multi-criteria decision framework with morphological, geometrical, and statistical membership functions. Use when: hyperspectral image anomaly detection, quantum neural network for remote sensing, fuzzy computing for image processing, Einstein fuzzy operations, or hybrid quantum-classical image analy...Votes: 0GitHub stars: 3
- Hyperbolic Gcn Brain NetworkHyperbolic Graph Convolutional Network (Brain-HGCN) for brain functional network analysis using Lorentz model and signed aggregation for excitatory/inhibitory connections. Activation triggers: hyperbolic GNN, brain network, fMRI analysis, geometric deep learning, Lorentz model.Votes: 0GitHub stars: 3
- Hyperbolic Learning Brain GraphsHyperbolic Learning on Brain Graphs (HLBG) framework for brain disorder diagnosis. Uses Lorentzian hyperbolic space to model hierarchical relationships among ROIs, functional communities, and whole-brain network. Introduces Graph-aware Mamba (GaMamba) for capturing long-range dependencies while preserving graph topology. SOTA on ABIDE-I (autism) and REST-MDD (depression) datasets. Use when: brain network analysis for disorder diagnosis, hyperbolic graph learning, brain functional connectivity...Votes: 0GitHub stars: 3
- Hyperbolic Neural MappingHyNeuralMap framework for mapping visual semantics to neural hierarchies using hyperbolic Lorentz geometry. Provides cross-modal semantic alignment in negative-curvature space, outperforming Euclidean baselines for fMRI-visual representation learning. Use when working with: hyperbolic embeddings, vision-neural mapping, cross-subject fMRI alignment, hierarchical semantic organization, Lorentz model, geometric deep learning for neuroscience, or neural representation learning with non-Euclidean ...Votes: 0GitHub stars: 3
- Hyperbolic Neural Population Geometry ComputationHyperbolic geometry framework for hippocampal neural population activity. Provides theoretical construction of hyperbolic tuning curves, connects neural decoding to associative memory via Modern Hopfield Network, and introduces hyperbolic-space associative memory with significantly larger capacity. Use when studying hippocampal encoding, hyperbolic cognitive maps, memory capacity optimization, or neural population geometry.Votes: 0GitHub stars: 3
- Hyperdimensional Stdp ComputingHyperdimensional computing with STDP equivalence methodology. Path-dependent semantic selection mechanism emerges equivalent to spike-timing-dependent plasticity in Galois-field based HDC. 激活词: hyperdimensional computing, HDC STDP, sparse distributed memory, VaCoAl, 高维计算Votes: 0GitHub stars: 3
- Hypergraph Functional Brain NetworkExtract high-order functional brain network features using hypergraph modeling. Goes beyond pairwise connectivity to capture multi-region interactions.Votes: 0GitHub stars: 3
- Hypergraph Markov MemoryTensor-based framework for higher-order Markov chains with memory on hypergraphs. Use when modeling complex systems with group interactions, memory effects, non-pairwise connections, or analyzing higher-order networks. Keywords: hypergraph, Markov chains, memory, tensor, higher-order networks, complex systems, random walks.Votes: 0GitHub stars: 3
- Ia Rag Interval Algebra TemporalHierarchical temporal RAG using Allen's Interval Algebra for formal temporal constraint reasoning with Interval Event Units (IEUs) organized in Thematic ForestVotes: 0GitHub stars: 3
- Iamb Matrix CliMatrix CLI operations for iamb including account registration, token retrieval, and Space management.Votes: 0GitHub stars: 3
- Ic Based Encoding BrainIndependent Component (IC)-based encoding models for linking continuous stimulus features to fMRI brain activity. Dissociates stimulus-driven and noise-driven signals using ICA decomposition. Trigger words: IC-based encoding, independent component, fMRI encoding, story comprehension.Votes: 0GitHub stars: 3
- Identity Trap Eeg Foundation ModelsEEG基础模型的身份陷阱诊断审计框架。FMScope协议用于诊断EEG基础模型是否陷入身份陷阱（subject identity shortcut），提供五项诊断指标分离真实生物标志物与身份特征。Votes: 0GitHub stars: 3
- Iit Critical ReviewCritical review framework for Integrated Information Theory (IIT). Provides systematic methodology for evaluating IIT's theoretical foundations, mathematical formalism, empirical predictions, and philosophical implications. Addresses ongoing debates about consciousness metrics and neural correlates.Votes: 0GitHub stars: 3
- Implicit Behavioral Decoding Spike ForecastsImplicit behavioral decoding from next-step spike forecasts at population scale. A single Mamba forecaster trained only on next-step spike counts at Neuropixels scale can deliver both neural population forecasts and behavioral state readouts in one forward pass. Activation: behavioral decoding, spike forecasting, Mamba neural population, Neuropixels, closed-loop BCI, implicit readout, spike prediction, population neural modelsVotes: 0GitHub stars: 3
- Impurity Model Quantum ComputationImpurity Hamiltonian analysis for quantum computation universality. Studies time evolution of fermionic systems with O(1) interacting modes and O(N) bath modes. Use when: (1) Analyzing impurity Hamiltonian universality for quantum computing, (2) Studying time-dependent vs time-independent quantum evolution, (3) Investigating fermionic mode interactions with quartic couplings, (4) Comparing classical simulability vs quantum computational power.Votes: 0GitHub stars: 3
- In Context Brain DecodingMeta-learning approach for training-free cross-subject brain decoding from fMRI. Enables zero-shot generalization to novel subjects by conditioning on few image-brain activation examples. Use when working with: (1) Cross-subject fMRI decoding, (2) Meta-learning for neuroscience, (3) Visual reconstruction from brain signals, (4) Subject-invariant neural representations. Activation: brain decoding, meta-learning fMRI, cross-subject decoding, in-context brain mapping.Votes: 0GitHub stars: 3
- Inexact Graph Matching Brain NetworksInexact Graph Matching for Brain NetworksVotes: 0GitHub stars: 3
- Infant Sensorimotor Motion RetargetingFramework for simulating infant first-person sensorimotor experience via motion retargeting from babies to humanoids. Reconstructs 3D infant pose from video and maps onto developmental robotics platforms (iCub, pyCub, EMFANT, MIMo). Activation: infant sensorimotor, motion retargeting, developmental robotics, humanoid infant simulation, sensorimotor experience, developmental neuroscience.Votes: 0GitHub stars: 3
- Infinite Horizon Stochastic Analysis无限视界随机系统分析方法论。核心思想：使用加权 L^p 空间、resolvent kernel 和测度变换处理无限时间跨度的随机优化问题。适用于长期决策、随机控制、无限视界规划。触发词：无限视界、随机系统、BSVIE、倒向随机 Volterra 积分方程、长期决策、infinite horizon、stochastic control、discounted problem。Votes: 0GitHub stars: 3
- Quantum Crypto AgilityIntent-based cryptographic API design for post-quantum cryptography (PQC) migration — cryptographic agility patterns for large software portfolios.Votes: 0GitHub stars: 3
- Quantum Data MiningQuantum data mining methodologies for information science — frequent itemset mining, quantum pattern discovery, and quantum-enhanced analytics on NISQ devices.Votes: 0GitHub stars: 3
- Quantum Network RoutingQuantum network routing and entanglement distribution using surface code error correction — reliable quantum communication over noisy channels.Votes: 0GitHub stars: 3
- Inhibitory Neuristor MitInhibitory neuristor based on metal-insulator transition. VO2-based inhibitory neuron for balanced neuromorphic computing. Activation: inhibitory neuristor, metal-insulator transition, VO2 neuron, balanced spiking.Votes: 0GitHub stars: 3
- Input Constrained Spatiotemporal TubesInput-constrained spatiotemporal tube (STT) control framework for safe navigation of unknown Euler-Lagrange systems in dynamic environments. Provides finite-time reach-avoid-stay guarantees with explicit actuator constraint handling. Approximation-free and computationally efficient.Votes: 0GitHub stars: 3
- Instruct Particulate 3d ArticulationInstruct-Particulate methodology for feed-forward 3D object articulation reconstruction using kinematic control. Enables scalable recovery of articulated 3D structures from single images or multi-view inputs. Use when: 3D articulation recovery, feed-forward 3D reconstruction, kinematic control for 3D objects, articulated object modeling.Votes: 0GitHub stars: 3
- Interbrain Networks GeometryGeometric framework for analyzing inter-brain networks in social neuroscience. Uses discrete geometry and curvature distributions to identify critical transitions in neural connectivity during social interactions, moving beyond correlation-based synchrony metrics. Activation: inter-brain networks, hyperscanning, social neuroscience, discrete geometry, curvature, network topology, synchrony, social interaction, EEG, fNIRSVotes: 0GitHub stars: 3
- Interdisciplinary DiscoveryDiscover interdisciplinary research connections using knowledge graph analysis (PageRank, Louvain, vector similarity). Use when analyzing cross-domain research, finding unexpected connections, or exploring interdisciplinary patterns. Keywords: 跨学科发现, interdisciplinary discovery, kg analysis, 知识图谱分析, find research connections, discover cross-domain patterns.Votes: 0GitHub stars: 3
- International Transfer Stochastic Cortical Self ReconstructionStochastic Cortical Self-Reconstruction (SCSR) framework for personalized mapping of gray matter atrophy in neurodegenerative disorders. Enables individualized healthy reference estimation directly from observed cortical thickness at vertex level, allowing detection of subtle subject-specific deviations. Evaluates generalization and transferability across populations (UK Biobank to Chinese dataset) with multiple training strategies and reconstruction backbones.Votes: 0GitHub stars: 3
- Internet Agentic Ai ArchitectureInternet of Agentic AI (IoAI) architecture patterns for scalable agent ecosystems — communication protocols, semantic interoperability, trust mechanisms, and governance frameworks. Use when: designing multi-agent systems, agent communication protocols, distributed AI coordination, agent identity/trust, semantic interoperability, large-scale agent networks.Votes: 0GitHub stars: 3
- Interpretable Eeg Biomarkers ParkinsonsInterpretable EEG biomarkers for Parkinson's disease detection using interpretable electrophysiological features of resting-state EEG. Captures cortical neural dynamics alterations for reliable non-invasive diagnosis and monitoring. Activation: EEG biomarker Parkinson's, interpretable EEG features, resting-state EEG, cortical neural dynamics, PD diagnosis.Votes: 0GitHub stars: 3
- Interpretable Meg Decoding Perceived SpeechInterpretable MEG decoding framework for perceived speech that combines spherical harmonics spatial attention, source-space mapping, and stimulus feature analysis to reveal what drives neural-to-audio retrieval. Use when implementing or analyzing MEG-based brain decoding systems, particularly for speech perception, neural source localization, or interpretable brain-computer interfaces.Votes: 0GitHub stars: 3
- Interpretable Ml Parkinsons Qsm FmriInterpretable machine learning methodology for predicting Parkinson's disease motor severity (MDS-UPDRS Part III) from neuroimaging features — Quantitative Susceptibility Mapping (QSM) MRI and multiband multiecho resting-state fMRI Regional Homogeneity (ReHo). Uses SVR, Elastic Net, Random Forest, XGBoost with nested CV and SHAP interpretability. Full multimodal model explains 45.4% variance. QSH+c clinical model achieves 75% within ±5 UPDRS points. Activation: Parkinson's prediction, QSM MRI...Votes: 0GitHub stars: 3
- Intrinsic Neuro Synaptic MemristiveMemristive networks intrinsic neuro-synaptic spiking dynamics methodology. Self-organizing circuits generating neuronal population dynamics similar to biological systems with nonlinear resonance phenomena. Trigger words: memristive, neuro-synaptic, spiking dynamics, resonance.Votes: 0GitHub stars: 3
- Intrinsic Noise Consolidation DoobDoob-Barrier-Conditioned Diffusion methodology for turning analog neuromorphic device noise into a continual-learning consolidation resource. Casts per-synapse consolidation as a Doob h-transform: condition each weight's stochastic dynamics on never crossing a memory-critical barrier. Activation: intrinsic noise consolidation, Doob barrier diffusion, noise as continual learning resource, neuromorphic consolidation, Doob h-transform synaptic, analog noise memory consolidation.Votes: 0GitHub stars: 3
- Intrinsically Stable Snn Bn FreeIntrinsically Stable SNN (IS-SNN) architecture for deep spiking neural networks without batch normalization. Removes activation-normalization layers via topology-aware weight standardization and offline reparameterization, restoring accumulation-only inference datapath. Achieves 68.05% ImageNet accuracy with 96.4% FPGA LUT reduction. Use when designing hardware-friendly deep SNNs, eliminating runtime normalization overhead, or analyzing firing-rate stability. Activation: IS-SNN, normalization...Votes: 0GitHub stars: 3
- Iot Cps Workflow SchedulingMulti-objective and multi-constrained IoT workflow scheduling in Edge-Hub-Cloud Cyber-Physical Systems using continuous-time mixed integer linear programming. Optimizes latency, energy, and reliability with selective task duplication. Activation: IoT scheduling, CPS workflow, edge computing, task scheduling, multi-objective optimization.Votes: 0GitHub stars: 3
- Iphoneme Brain To Text Als ConformerxliPhoneme brain-to-text communication system for ALS using ConformerXL phoneme decoder with gaze-assisted interface. Achieves 92.14% phoneme accuracy (7.86% PER) and 73.39% word accuracy on T15 intracranial EEG dataset. 180ms latency on CPU. Activation: brain-to-text, speech BCI, phoneme decoding, Conformer, ALS, intracranial EEG, iEEG.Votes: 0GitHub stars: 3
- Iris Visual Cortex Framework VitIRIS: A Visual Cortex-Inspired Framework for Analyzing Orientation Selectivity in Vision Transformers. Provides neuroscience-inspired metrics (RSS, ORS, orientation tuning bandwidth) to quantify how orientation selectivity emerges in ViTs and tracks biologically-grounded features during training. Use when analyzing low-level feature encoding in vision transformers, studying orientation selectivity, or probing representational geometry in transformer models.Votes: 0GitHub stars: 3
- Isi Adaptive Threshold Neuronal NetworksFirst-passage-time analysis of inter-spike interval (ISI) statistics for excitatory-inhibitory (EI) integrate-and-fire neurons with depolarizing and hyperpolarizing adaptive thresholds. Use when studying stochastic neuronal firing, ISI variability, adaptive threshold mechanisms, or EI balance effects on spike-time statistics.Votes: 0GitHub stars: 3
- Isi Cv Gradient Free Continual Learning SnnISI-CV: Inter-areal predictive coding for gradient-free continual learning in SNNs. Activation: gradient-free learning, continual learning, predictive coding.Votes: 0GitHub stars: 3
- Iterative Ising Qec DecoderIterative Low-Order Decoding (ILOD) methodology for quantum error correction — mapping QEC decoding onto ground-state optimization of classical Ising Hamiltonians with Bayesian prior-based cross-term approximation. Use when: implementing QEC decoders, optimizing quantum circuit error correction, reducing Ising model interaction order, or applying statistical mechanics approaches to quantum error correction. Activates on keywords: iterative Ising decoder, ILOD, quantum error correction decodin...Votes: 0GitHub stars: 3
- Itp Stdp Snn TrainingITP-STDP (Intrinsic-Timing Power-of-Two STDP) 方法论用于片上脉冲神经网络训练。通过算法和硬件级优化消除STDP计算开销，实现能耗效率和硬件资源利用的显著提升。Votes: 0GitHub stars: 3
- Jaynes Cummings Oscillator ControlUniversal Jaynes-Cummings (JC) based oscillator control methodology for bosonic quantum processors. Compiles arbitrary unitary gates into JC interaction sequences and qubit rotations for universal qudit control.Votes: 0GitHub stars: 3
- Jedi Neural Dynamics InferenceJEDI: Jointly Embedded Inference of Neural Dynamics - learning shared embeddings of RNN weights to infer neural population dynamics across tasks and contexts. Triggers: neural dynamics inference, RNN embedding, meta-learning, neural population, cross-task generalization.Votes: 0GitHub stars: 3