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Claude Skills by hiyenwong
github.com/hiyenwong9,934 skills5 installs19,223 views
- Longspike Fractional Order Snn State SpaceLongSpike fractional-order SSM for SNNs — enables efficient long-sequence learning in spiking neural networks using fractional calculus to extend memory capacity beyond traditional integer-order models.Votes: 0GitHub stars: 3
- Lonic Algorithm Hardware Codesign SnnLonic: INT4 algorithm-hardware co-design for SNNs. Energy-efficient fully local online SNN training methodology with algorithm-hardware co-optimization.Votes: 0GitHub stars: 3
- Loop Composition QuantumLoop composition methodology for quantum algorithms. Models program control flow (branching + looping) in quantum circuits using quantum walk formalism. Addresses limitations of straight-line quantum circuit model for variable-length subroutines in superposition. Use when designing quantum algorithms with dynamic control flow, variable-time search, or loop-based quantum computation. arXiv:2605.07518Votes: 0GitHub stars: 3
- Loss Biased QecLoss-biased fault-tolerant quantum error correction methodology using fast autoionization in alkaline-earth atoms. Implements practical fault-tolerant quantum computing with sub-millisecond QEC cycles and high encoding efficiency. Use when: (1) Analyzing loss-biased QEC papers, (2) Implementing quantum error correction with neutral atoms, (3) Designing ultra-fast QEC cycles, (4) Studying alkaline-earth atom-based quantum computing.Votes: 0GitHub stars: 3
- Lottery Bp DecodingLottery BP methodology for scalable quantum error correction decoding. Introduces randomness during belief propagation decoding to improve accuracy by 2-8 orders of magnitude for topological codes (surface, toric, BB codes). Use when: quantum error correction, qLDPC decoding, scalable quantum decoders, belief propagation for quantum codes, syndrome processing, PolyQec architecture, or when building fault-tolerant quantum computing systems requiring real-time decoding.Votes: 0GitHub stars: 3
- Low Frequency Alpha Visual Cortex RoutingLow-frequency (alpha-band) activity shapes fine-scale information routing in early visual cortex — alpha oscillations in V1 carry spatially specific figure-ground information and modulate inter-areal V1-V4 coupling during visual processing, supporting the hypothesis that alpha-band synchrony implements hierarchical feedback gating.Votes: 0GitHub stars: 3
- Low Rank Gluing CompositionalityMathematical framework for compositional computation in inhibition-dominated threshold-linear networks via low-rank gluing rules. Proves how structural modularity enables functional compositionality - component subnetworks' fixed points determine global network dynamics. Activation: compositionality, threshold-linear networks, TLN, fixed points, modular network, network assembly, gluing rules, low-rank coupling, inhibition-dominated, neural circuit design, computational primitivesVotes: 0GitHub stars: 3
- Lrm Game Learning Brain AlignmentBehavioral and brain alignment methodology between Large Reasoning Models (LRMs) and human game learners, using fMRI-validated complex gameplay datasets. Activation: LRM brain alignment, reasoning model cognitive neuroscience, AI human game learning, frontier model brain prediction, behavioral alignment fMRI.Votes: 0GitHub stars: 3
- Lsformer Local Structure Aware Spiking TransformerLSFormer: Local Structure-Aware Spiking Transformer. Replaces global self-attention with dilated local windows and spiking response pooling for energy-efficient SNNs. Keywords: spiking transformer, local attention, SNN, energy-efficient, LSFormer, spiking neural network, self-attention bottleneck, SPooling, LS-SSA, Tiny-ImageNetVotes: 0GitHub stars: 3
- Madcle Multi Atlas Disentangled ConnectivityMulti-Atlas Disentangled Connectivity LEarning (MADCLE) methodology for brain disorder identification from functional connectivity (FC) matrices. Addresses atlas dependency heterogeneity by jointly encoding FC matrices from different brain atlases with cross-atlas distributional alignment, covariate similarity supervision, and decorrelation constraints. Use when working with multi-atlas fMRI FC analysis, cross-atlas consistency learning, brain disorder classification (ADNI, ADHD-200), disenta...Votes: 0GitHub stars: 3
- Magic Informed Quantum Architecture SearchMagic-Informed Quantum Architecture Search (QAS) methodology using Monte Carlo Tree Search with Graph Neural Networks for quantum circuit design. Use when designing quantum circuits with controlled nonstabilizerness (magic) levels, when optimizing quantum architecture search, when applying AlphaGo-style MCTS to quantum problems, when estimating magic properties of quantum circuits using GNNs, or when searching for optimal quantum circuit structures balancing magic resource requirements.Votes: 0GitHub stars: 3
- Magiq Post Quantum Agent GovernanceMulti-agent AI governance system with provable post-quantum security (MAGIQ framework). Defines and enforces communication/access-control policies for agent-to-agent sessions using quantum-resistant cryptography with UC security proofs. Use when: post-quantum agent security, multi-agent governance, quantum-resistant multi-agent systems, agent accountability, SAGA framework comparison, UC framework multi-agent security, NIST PQC agent policies. Triggered by: MAGIQ, post-quantum agentic AI, qua...Votes: 0GitHub stars: 3
- Magnet Brain Structure Function GnnMulti-Scale Adaptive Graph Network (MAGNet) for learning structural-functional brain representations. Models structure-function coupling for cognitive insight.Votes: 0GitHub stars: 3
- Making Claude ChemistMethodology from Anthropic research (Jun 2026) on benchmarking LLM capability for chemistry tasks, specifically NMR spectral analysis and molecular structure elucidation. Opus 4.7 achieves competitive accuracy with ChemDraw/MestReNova on hydrogen NMR (±0.079 ppm error), carbon NMR, peak shape prediction, and 1D inverse structure elucidation. Use when evaluating LLM performance for chemistry workflows, building AI-assisted molecular analysis tools, or understanding chemistry-specific AI benchm...Votes: 0GitHub stars: 3
- Mamba Spike Behavioral DecodingMamba forecaster methodology for implicit behavioral decoding from next-step spike forecasts at population scale. A single sequence model trained only on next-step Poisson rate prediction produces predicted firing rates that decode animal behavior better than raw spike counts under matched temporal context. Enables closed-loop BCI without separate behavioral decoding networks.Votes: 0GitHub stars: 3
- Mamba Spike Forecaster BciImplicit Behavioral Decoding from Next-Step Spike Forecasts at Population Scale — using a single Mamba state-space model trained only on next-step spike counts (Neuropixels scale) to simultaneously forecast neural population activity and decode behavioral state via lightweight linear readout. arXiv: 2605.12999Votes: 0GitHub stars: 3
- Mamba Spike Forecasting Behavioral DecodingImplicit Behavioral Decoding from Next-Step Spike Forecasts at Population Scale — Mamba forecaster methodology for closed-loop BCI. A single Mamba model trained on next-step spike counts at Neuropixels scale simultaneously predicts future neural activity and decodes behavioral state via a lightweight linear readout. Use when: analyzing neural population spike data, building closed-loop BCI decoders, applying state-space models (Mamba/SSM) to neural time series, or studying implicit behavioral...Votes: 0GitHub stars: 3
- Mamba Spike Population ForecasterMamba-based spike forecaster methodology for closed-loop BCI. A single Mamba model trained on next-step spike counts at Neuropixels scale simultaneously predicts neural activity and decodes behavioral state, outperforming linear decoders on raw spikes. arXiv: 2605.12999 (May 2026).Votes: 0GitHub stars: 3
- Many Body Chirality StabilizerMany-body chirality methodology for topological stabilizer states — formulated as obstruction to complex conjugation via finite-depth local operations, with four-partite obstruction and intrinsic imaginarity.Votes: 0GitHub stars: 3
- Many Body Super SubradianceMany-body super- and subradiance in ordered atomic arrays. Studies collective light-matter interactions in subwavelength-spaced atom arrays with programmable photon-mediated interactions. Activation: superradiance, subradiance, ordered atomic arrays, many-body quantum opticsVotes: 0GitHub stars: 3
- Mass Conservation Nca Reservoir CriticalityMass conservation as inductive bias for self-organized criticality in neural cellular automata reservoirs. Demonstrates 1.27× faster evolution with comparable downstream performance. Activation: self-organized criticality, neural cellular automata, reservoir computing, mass conservation, criticalityVotes: 0GitHub stars: 3
- Mast Aigv Detection SnnMAST (Multi-channel pseudo-event SNN with Adaptive Spiking Temporal integrators) — first SNN-based detector for AI-generated videos. Converts inter-frame residuals into pseudo-events processed by spike-driven temporal branch with learnable per-channel time constants, fused with frozen X-CLIP semantic trajectory encoder. Achieves 93.14% cross-generator accuracy on GenVideo. Activation: AI-generated video detection, SNN video detection, temporal artifact detection, pseudo-event conversion, cros...Votes: 0GitHub stars: 3
- Mathematical QuantizationKohn-Nirenberg quantization and Lie group quantization methods. Construct unitary dual 2-cocycles for semidirect products like affine group. Frobenius seaweed Lie algebra applications. Use when: (1) Quantizing Lie groups (affine, semidirect products), (2) Constructing unitary cocycles for representation theory, (3) Implementing Kohn-Nirenberg quantization procedure, (4) Studying Frobenius seaweed Lie algebra structures.Votes: 0GitHub stars: 3
- Non Euclidean Visual Space Information GeometryInformation geometry framework for analyzing non-Euclidean structure of visual space — modeling perceptual geometry using Riemannian manifolds, Fisher information, and Finsler geometry. Activation: visual space, non-Euclidean, information geometry, Riemannian manifold, perceptual geometry, Fisher information, visual perception, psychophysics.Votes: 0GitHub stars: 3
- Temporal Interference Stimulation MathematicalMathematical framework for analyzing Temporal Interference Stimulation (TIS) using FitzHugh-Nagumo model with phase-plane analysis and geometric singular perturbation theory. Use when: modeling non-invasive neuromodulation, analyzing TIS neural activation, designing deep brain stimulation protocols, bifurcation analysis of driven neurons, phase-plane analysis of oscillatory stimulation. Activation: temporal interference stimulation, TIS neuromodulation, FitzHugh-Nagumo TIS, geometric singular...Votes: 0GitHub stars: 3
- Tensor Cookbook DiagramsTensor network diagram methodology for simplifying tensor algebra - graphical notation for contractions, decompositions, and gradient computation bridging quantum physics notation with machine learning. Activation: tensor network diagrams, tensor cookbook, penrose notation, tensor contraction diagrams, 张量网络图, 张量图解.Votes: 0GitHub stars: 3
- Vo2 Conduction Topology Phase DynamicsElectrically steered conduction topologies and period-doubling phase dynamics in VO2 devices. Phase transition control for next-generation computing platforms. Activation: VO2 topology, phase dynamics, conduction steering, insulator-metal transition.Votes: 0GitHub stars: 3
- Maximum Entropy Neural ConnectivityMaximum entropy principle for neural network connectivity — normative framework for understanding how task constraints shape neural connectivity structure without gradient descent.Votes: 0GitHub stars: 3
- Mbbn Multiband Brain NetworkMulti-Band Brain Net (MBBN) — Transformer-based framework for frequency-specific spatiotemporal brain dynamics from fMRI. Integrates biologically-grounded frequency decomposition with multi-band self-attention for cognitive and psychiatric applications. Use when analyzing frequency-dependent brain network interactions, building fMRI-based prediction models for psychiatric disorders (depression, ADHD, ASD), or developing scale-aware neural biomarkers.Votes: 0GitHub stars: 3
- Mcap Multilevel Covariance RegressionMultilevel Covariate-Assisted Principal Regression (MCAP) for brain functional connectivity analysis. Handles hierarchically nested neuroimaging data, identifies cluster-specific projections, and models covariance matrix outcomes with subject-level covariates. Use when: analyzing lifespan brain connectivity, multilevel fMRI data, functional connectivity regression, covariance matrix outcomes.Votes: 0GitHub stars: 3
- Mckinsey 39 Work Habits麦肯锡工作法39个工作习惯——结构化问题解决、高效沟通、时间管理与持续成长的方法论Votes: 0GitHub stars: 3
- Mcts Encoding Discovery QmlMonte Carlo Tree Search (MCTS) methodology for discovering optimal data encoding circuits in quantum-classical neural networks. Addresses the open question of why certain quantum data encodings outperform others by treating encoding circuit design as a sequential decision problem. Use when: quantum data encoding optimization, MCTS quantum circuits, quantum-classical neural network design, QML encoding strategy, quantum feature map discovery.Votes: 0GitHub stars: 3
- Mcts Quantum Encoding DiscoveryMCTS-based quantum data encoding discovery methodology. Use Monte Carlo Tree Search to discover optimal data encoding circuits for quantum-classical neural networks. Evaluates encoding strategies by effective rank correlation rather than entanglement capability or Fourier decomposition. Applies to QML model design, encoding circuit optimization, and quantum feature map selection. Activation: MCTS encoding discovery, quantum encoding optimization, Monte Carlo Tree Search QML, data encoding cir...Votes: 0GitHub stars: 3
- Mean Field Adaptation Oscillations**arXiv**: [2606.30366v1](https://arxiv.org/abs/2606.30366v1) **Authors**: Bowen W. Zheng, Earl K. Miller, Ila R. Fiete (MIT) **Date**: June 29, 2026 **Keywords**: mean-field theory, oscillatory dynamics, adaptation, low-rank networks, chaotic dynamicsVotes: 0GitHub stars: 3
- Mean Field Low Rank Adaptation OscillationsDynamical mean-field theory for low-rank recurrent networks with firing-rate adaptation. Identifies four oscillatory regimes and bifurcation mechanisms linking chaos, Hopf bifurcation, and noise-sustained oscillations to biological rhythms (Up-Down states, waxing-and-waning episodes).Votes: 0GitHub stars: 3
- Mean Field Molecular Brain BridgeMean-field models bridging molecular to brain scales.Votes: 0GitHub stars: 3
- Mean Field Multi Scale Brain ModelsUse when bridging molecular to brain scales.Votes: 0GitHub stars: 3
- Mean Field Oscillatory Dynamics Low Rank AdaptationThis paper develops a dynamical mean-field theory for random recurrent networks with low-rank structure and firing-rate-driven adaptation. The theory reveals how adaptation strength drives networks through four distinct dynamical regimes, providing a unified framework for understanding biological oscillations observed during wakefulness, sleep, and anesthesia.Votes: 0GitHub stars: 3
- Mean Field Oscillatory Dynamics Low Rank NetworksDynamical mean-field theory for random recurrent networks with low-rank structure and firing-rate-driven adaptation. Identifies four oscillatory regimes: static coherent, noise-sustained oscillations, stochastic switching, global limit cycle. Explains waxing-waning rhythms, Up-Down alternations observed in wakefulness/sleep/anesthesia. Trigger words: mean-field theory, oscillatory dynamics, low-rank recurrent network, Hopf bifurcation, adaptation, neural oscillations, Up-Down states.Votes: 0GitHub stars: 3
- Measurement Based Quantum PcaMeasurement-based soft PCA framework using entropy-regularized Fermi-Dirac filters for quantum principal component analysis without eigenvector recovery. Enables dimension-independent sample complexity O(1/eta^2) for fractional-rank scoring. Use when: quantum PCA, soft PCA, Fermi-Dirac filter, measurement-based PCA, quantum data analysis, eigenvector-free PCA, anomaly detection via PCA, spectral energy profiling.Votes: 0GitHub stars: 3
- Measuring Llms Impact N Day ExploitsAnthropic research (Jun 8, 2026) — Measuring how LLMs dramatically accelerate N-day exploit development; Claude Mythos Preview built 8 working Firefox exploits autonomously and 8 Windows kernel privilege escalation chains, collapsing the historically slow patch-diffing bottleneck.Votes: 0GitHub stars: 3
- Measuring Llms Impact On N Day ExploitsMeasuring LLMs’ impact on N-day exploitsVotes: 0GitHub stars: 3
- Mechanistic Bridges Receptors Whole Brain DynamicsFramework for receptor-aware whole-brain modeling that bridges molecular/synaptic scales to whole-brain recordings through mean-field reductions, with explicit validity domains and computational trade-offs.Votes: 0GitHub stars: 3
- Medical Ai DiagnosisPatterns for building AI-based medical diagnosis systems with clinical explainability. Covers foundation models for medical imaging, clinical reasoning trace generation, multi-modal patient data integration, and explainable AI for healthcare. Use when building medical AI diagnosis tools, clinical decision support systems, explainable medical ML models, or medical foundation models. Trigger: medical AI, clinical diagnosis AI, explainable healthcare, medical foundation model, DeepMedix, clinica...Votes: 0GitHub stars: 3
- Adaptive Hybrid Feature Fusion MedicalAdaptive Hybrid Quantum-Classical Feature Fusion methodology for medical image classification. Addresses optimization asymmetries between quantum and classical paradigms using Temperature-Scaled Hybrid Fusion (TSHF), Dynamic Hybrid Fusion (DHF), and Static Hybrid Fusion (SHF) strategies. Use when designing hybrid quantum-classical ML pipelines for healthcare/medical imaging, especially when combining ResNet backbones with variational quantum circuits for diagnostic tasks.Votes: 0GitHub stars: 3
- Neuroclaw Multimodal NeuroimagingNeuroClaw - Domain-specialized multi-agent research assistant for executable and reproducible neuroimaging research. Supports heterogeneous modalities (sMRI, fMRI, dMRI, EEG), BIDS metadata integration, environment management, and three-tier skill/agent hierarchy. Use for automated neuroimaging pipelines, reproducible research workflows, and multi-modal brain data analysis. Keywords: neuroimaging, BIDS, multi-agent, reproducible research, fMRI, sMRI, dMRI, EEG.Votes: 0GitHub stars: 3
- Neuromorphic Power Converter HealthNeuromorphic parameter estimation for power converter health monitoring using spiking neural networks. Real-time fault detection and degradation assessment for industrial power electronics with event-driven processing. Keywords: power converter health, SNN fault detection, neuromorphic monitoring, parameter estimation, condition monitoring.Votes: 0GitHub stars: 3
- Membrane Potential Alignment Intracortical BciMembrane Potential Alignment (MPA) - Test-time adaptation method for spiking neural networks in intracortical brain-computer interfaces. Realigns pretrained decoders to shifted neural recordings by matching membrane potential distributions via KL divergence - computationally efficient for implantable hardware. Activation: test-time adaptation, intracortical BCI, membrane potential alignment, SNN adaptation, neural signal shift, KL divergence matching, unsupervised adaptation.Votes: 0GitHub stars: 3
- Self Evolving MemorySelf-evolving memory architecture for AI agents that learn across interactions without training. Use when building agents that need to: (1) accumulate experience across cases, (2) correct recurrent reasoning mistakes via reflection, (3) adapt tool-use behavior dynamically. Applicable to medical diagnosis, code debugging, customer support, research analysis, and any domain where agents solve repeated similar tasks. Trigger: self-evolving memory, inter-case learning, agent memory, episodic memo...Votes: 0GitHub stars: 3
- Vacoal Algebro Deterministic MemoryAlgebro-deterministic hippocampal memory architecture (VaCoAl) built from Galois-field LFSRs. Provides substrate-level alternative to random scaffold-to-hippocampus projections, algebraically tractable model of multi-hop replay-fidelity decay, and STDP-like path selection. Based on Chuma, Otsuka & Sato (arXiv: 2605.15652). Use when designing brain-inspired memory systems, implementing hippocampal replay mechanisms, building hippocampus-silicon bridge architectures, or modeling memory consolid...Votes: 0GitHub stars: 3