Menu
Skills in this repository
SkillsMP has collected 4,114 skills from hiyenwong/ai_collection. Open a skill to review its source and details.
hiyenwong/ai_collectionShowing 40 of 4,114 collected skills.
Quantum statistical estimation theory and applications - combines Bayesian methods, quantum Cramér-Rao bounds, and quantum parameter estimation for optimal quantum system state estimation. Use when analyzing quantum metrology, quantum parameter estimation,…
Quantum systems control theory and simulation framework. Covers coherent feedback control (H∞), physics-informed discrete-event simulation for quantum networks, and high-dimensional quantum photonics encoding. Use when: (1) designing control systems for…
Quantum tensor network simulation optimization with PTSBE (Pre-Trajectory Sampling with Batched Execution). Accelerates quantum trajectory methods for noisy quantum systems. Use when: (1) Simulating noisy quantum circuits, (2) Optimizing tensor network…
Quantum algorithms for topological data analysis (TDA) - persistent Betti numbers, simplicial complexes, Vietoris-Rips topology, high-dimensional feature extraction. Use when analyzing quantum approaches to TDA, persistent homology, Betti number estimation,…
Exact framework for computing heat, energy, and particle transport statistics in quadratic quantum systems coupled to Gaussian reservoirs — combines full counting statistics with non-Markovian master equations. Use when: analyzing quantum transport in…
Semiclassical methods connecting quantum statistical mechanics to analytic number theory. Uses trace formula and periodic orbit theory to study integer partitions. Activation: semiclassical, integer partitions, density of states, number theory, periodic…
Shunting inhibition and dendritic branching reshape local credit assignment geometry. Shows how E/I conductance + dendritic tree structure enable biological neurons to approximate backprop with restricted somatic feedback. By Safaai, Richards & Sabatini…
Sparse Identification Graph Neural Network (SIGN) for inferring governing equations of complex networked systems. Use when working with: (1) complex systems dynamics prediction, (2) equation discovery from data, (3) graph neural networks for networked…
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
Meta-skill that extracts reusable skill patterns from conversations and generates standard SKILL.md files.
Spiking Neural Networks for online data reduction in high-energy physics detectors. Temporal-coincidence encoding and distributed SNN architecture for the ePIC dRICH detector at the Electron-Ion Collider. Achieves 5x data reduction while preserving genuine…
Spectral entropy diagnostic S(K)/log n for quantum Gaussian process kernels. Unified framework showing dequantization and posterior pathologies governed by same quantity. Proves Cauchy-Schwarz tail bound on Nystrom error, variance-contraction identity,…
First comprehensive evaluation of SNNs for real-world automotive multi-object detection and tracking using SpikeYOLO transfer learning. Achieves mAP 0.937 (KITTI) and 0.771 (BDD100K MOT2020) for detection, HOTA 0.701/0.445 for tracking — competitive with…
Statistical interpretation framework unifying algebraic quantum mechanics and quantum probability theory — links observable algebras to measurement statistics for foundations of quantum physics. Use when: analyzing measurement procedures statistically,…
Systems engineering research synthesis covering April-May 2026 arXiv papers. April 2026 methodologies: (1) Situation-aware feedback-predictive control for autonomous vehicles, (2) Heterogeneous dual-network UAV coordination, (3) Multi-agent RL for 3D…
Operational reformulation of quantum mechanics via transformation-response framework. A quantum state is the catalog of responses to all physical transformations, characterized by a positive-definite characteristic function on the local group. From this…
"Updating the standard neuron model in artificial neural networks - replacing the simplistic point neuron model with more realistic cortical cell representations"
[TODO: Complete and informative explanation of what the skill does and when to use it. Include WHEN to use this skill - specific scenarios, file types, or tasks that trigger it.]
Zero-shot Quantum Neural Architecture Search methodology for VQA circuit optimization without classical search loop. Use when: (1) designing variational quantum circuits, (2) optimizing quantum architecture without expensive search, (3) reducing classical…
Integration testing patterns for autonomous agent frameworks — mocking LLM routers, verifying tool-use loops, contract validation, and fallback chains. Applies to super_factory and similar spec-driven agent architectures.
Dynamic neural manifolds methodology for flexible closed-loop control on neuromorphic hardware. Uses sensory inputs to modulate heterogeneous inhibition, gain, and transient currents, driving rapid subspace rotations to switch between behaviors and…
Dynamic neural manifolds methodology for flexible closed-loop control on neuromorphic hardware. Spiking ring networks with control knobs (gain, inhibition, transient currents) that steer low-dimensional manifold geometry for explainable autonomous behavior.…
Hyperbolic Learning on Brain Graphs (HLBG) methodology for brain disorder diagnosis using Lorentzian hyperbolic space and Graph-aware Mamba (GaMamba). Models hierarchical relationships among ROIs, functional communities, and whole-brain networks via geometric…
Quantum Optimization via Coordinate Descent (QUACOD) methodology. Decomposes large-scale combinatorial optimization problems into quantum-solvable subproblems using coordinate descent, enabling NISQ-era hardware to handle problems 5-35x larger than direct…
Digital twin framework for quantum neuromorphic cognitive modeling - combining quantum reservoir computing with tensor networks for emotional memory and thermodynamic-aware learning
Comprehensive survey of single-entity spiking neuron models - mathematical modeling approaches for biologically plausible neural systems including discrete/continuous models, membrane potential dynamics, and various neural components
Comprehensive survey of single-entity spiking neuron models covering mathematical formulations, biological plausibility, and computational trade-offs. Covers integrate-and-fire variants (LIF, EIF, Izhikevich, AdEx), Hodgkin-Huxley models, FitzHugh-Nagumo,…
Soliton-like wave propagation in 2D recurrent SNNs with weighted STDP - minimal biologically plausible spiking model combining multiplicative STDP, divisive normalization, homeostatic threshold adaptation, and refractory period to produce self-propagating…
Topology-Dependent Emergence of Polychronous Neuronal Groups via Recurrence Plot characterization. Analyzes how small-world network topology drives PNG formation in spiking networks with STDP and heterogeneous delays.
Free-probability approach to stationary covariance spectra of discrete-time non-normal random recurrent dynamics - derives closed functional equation for moment generating function of limiting stationary covariance spectrum, analyzes tail eigenvalue behavior…
Pan-Organ Foundation Model (Pan-FM) for multimodal biomedical imaging with missing-organ robustness. Pre-trained on seven organs (Brain, Heart, Adipose, Liver, Kidney, Spleen, Pancreas) using Saliency-Guided Masking (SGM) to prevent dominant-organ shortcut…
Krylov Mean-Field Chaos theory for random recurrent networks — demonstrating that deterministic chaos has latent predictability through Krylov state space decomposition. Extends Hamiltonian chaos concepts to classical dissipative systems.
Quantum Fisher Information estimation under decoherence via MCMC sampling — maps QFI lower bounds onto classical expectation values over wave function amplitude distributions. Enables QFI estimation for system sizes beyond exact diagonalization. Use when:…
Extract reusable research skill patterns from knowledge graph paper analysis. Uses PageRank, Louvain, and vector search to identify important papers and research clusters, then distills patterns into new skills. Activation: extract research pattern, research…
Source text: Mixed languages
Small-gain analysis for large-scale distributed systems - exponential incremental i-IOSS stability via local subsystem conditions. LMI-based stability analysis for nonlinear distributed systems. Activation: distributed stability, small-gain theorem, i-IOSS,…
Analyze Spiking Neural Network (SNN) papers, extract technical patterns from knowledge graph, and identify reusable research methodologies for neuromorphic computing.
Surviving by Serving (SBS) principle for self-organization in complex adaptive systems - components persist when their outputs are utilized by others, prolonged non-utilization promotes adaptation. Minimal multi-agent model where agents transform shared…
Distributed fault discrimination in microservice architectures using joint temporal-structural representation learning. Models microservice operations as dynamic graph sequences, combines temporal GNN encoding with attention-based structured message passing,…
Tensor Network Feature Engineering methodology for multi-class neurological disorder prediction from MRI data. Uses tensor network decompositions to extract high-dimensional features from sparse medical imaging. Activation: tensor network MRI, neurological…
Uncertainty-Guided Hypergraph Refinement (UGHR) methodology for medical image segmentation. Uses entropy-based uncertainty maps from coarse predictions to spatially guide targeted refinement in boundary/transition regions. Decouples foreground/background…