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.
Time series analysis plays a vital role across a wide range of scientific and engineering domains but poses substantial computational challenges. A major difficulty arises from the time reparameteriza. Based on arXiv:2607.07634.
Nonlinear dynamics is ubiquitous in nature, ranging from chemical pattern formation to ocean circulation, yet its simulation on quantum computers is fundamentally limited by the unitary nature of quan. Based on arXiv:2607.07338.
Artificial intelligence (AI) is a double-edged sword: while it has achieved remarkable success across a wide range of domains, its deployment also calls for effective oversight and regulation, for whi. Based on arXiv:2607.07527.
Assigning Common Weakness Enumeration (CWE) categories to Common Vulnerabilities and Exposures (CVE) records remains an important but largely manual step in vulnerability analysis. We study this task. Based on arXiv:2607.07573.
Generating signals on graphs requires permutation-equivariant models that exhibit stability with respect to relative structural perturbations. While favorable stability properties of Graph Neural Netw. Based on arXiv:2607.07510.
In biological circuits, sequential neural activity evolves along dynamic, low-dimensional manifolds to enable flexible behavior. Spiking network models link aspects of this sequential activity to feat. Based on arXiv:2607.07373.
In this work, we reviewed different approaches in mathematical modeling of biologically plausible neural systems. Models are characterized and classified based on their common features and special use. Based on arXiv:2607.07429.
Navigation for social organisms rarely is a fully independent activity. Group structure and dynamics, as well as embodied interactions, critically influence useful behavior. Individual neural network. Based on arXiv:2607.07460.
We present EmbodiedGen V2, a generative 3D world engine for building executable sim-ready environments for embodied intelligence. Sim-ready 3D asset generation has advanced rapidly, yet assembling suc. Based on arXiv:2607.07459.
Benchmarking neural network architectures for scalable Quantum State Tomography with memristor-based acceleration patterns
Sample-Adaptive Hyperbolic Graph Neural Network for EEG-based depression recognition. Uses hyperbolic geometry to capture hierarchical brain network structure and personalized functional connectivity.
Onnes methodology — physics-grounded digital twin simulator driving multi-agent LLM operations layer for cryogenic fault diagnosis. Combines forward physics model with learned noise fingerprint, enabling zero-shot fault classification via contrastive few-shot…
Lattice surgery compilation methodology for color codes using pipe diagrams — extends surface-code pipe diagram framework to triangular color codes on 6.6.6 lattice. Enables distance-independent spacetime optimization, correlation surface realization, and…
Finite Reliability Representations (FRR) methodology for noise-calibrated belief-space covers in decision-making systems. Provides certified suboptimality bounds based on sensing, process, and actuation noise. Use when designing reliable decision systems,…
Initialization-free Bernstein-Vazirani (IF-BV) algorithm methodology allowing arbitrary ancilla states as oracle register to improve probabilistic BV performance. Derives explicit formula for IF-BV performance, necessary and sufficient conditions for maximal…
Rigorous mathematical framework for analyzing metastability in stochastic spiking neural networks using the pathwise approach. Reviews Galves-Löcherbach (GL) models, connecting statistical physics to neural dynamics. Covers metastable state transitions,…
Progressive crystallization methodology for turning AI agent exploration into deterministic, lower-cost workflows. Three-stage execution taxonomy with evidence-based promotion/demotion mechanism. (arXiv: 2607.07052)
Strictly local tile-code architectures for quantum error correction on 2D planar lattices. Tile codes are planar qLDPC codes with weight-6 stabilizers and open boundary conditions, offering up to 4x encoding efficiency vs. surface code. Uses SWAP-based…
Wigner function reconstruction methodology for continuous-variable quantum system characterization. Combines provably efficient regression for sparse states (binomial codes, cat states) with deep learning for general states (GKP). Use when: (1) characterizing…
Mechanism for time-axis selection in quantum systems via Hermitian inner product choice — identifies the symmetry-breaking step that selects future-timelike axis and locates Born rule as projection onto that axis. Applicable to quantum foundations, Lorentz…
Adaptive confidence-gated quantum error correction decoding methodology. Two-stage inference: lightweight neural fast-path + MWPM refinement for latency-constrained QEC systems. Use when designing real-time quantum decoders, hardware-aware QEC co-design, or…
Bosonic quantum error correction with finite stellar rank — establishes stellar rank as an operationally meaningful resource measure for bosonic QEC under practical state-preparation constraints. Use when designing bosonic codes, analyzing non-Gaussian…
Simplified coherent feedback H∞ control design for linear quantum systems using Lyapunov equations instead of coupled algebraic Riccati equations — computationally efficient robust control for quantum optical systems.
Parameter-efficient Continuous-Variable Photonic Quantum Neural Networks (CV-QNN) for edge medical AI applications. Covers room-temperature quantum computing on photonic hardware, MobileNet feature extraction + PCA dimensionality reduction, and CV-QNN…
Parameter-efficient Continuous-Variable Photonic Quantum Neural Networks for Edge AI — simplified Φ∘D∘U₁ CV-QNN architecture achieving 100% calibrated test accuracy on oral cancer detection with only 18 parameters (44% fewer than standard CV-QNN layer). Use…
Data-driven system identification methods for quantum dynamics, using machine learning to learn accurate models of quantum system behavior from experimental data. Enables model-based control design without requiring first-principles quantum mechanical…
Distributed Quantum Fourier Transform (QFT) circuit optimization — circuit partitioning for distributed quantum systems using teleportation to minimize e-bit consumption.
End-to-end learning of quantum control on latent dynamical manifolds — replaces iterative simulate-then-optimize with joint LSTM-based dynamics and control strategy learning.
PAC-Bayesian generalization theory for quantum reinforcement learning. Analyzes entanglement as structural complexity axis via Fisher effective dimension. Use when evaluating generalization of quantum policies, designing PQCs for RL, or studying…
Geometric obstruction framework for multiparameter quantum estimation — proves when simultaneous t² scaling fails and provides a computable diagnostic via Gram matrix of diagonal generators. Use when designing multiparameter quantum sensors, analyzing quantum…
Model Predictive Control (MPC) methodology applied to quantum state preparation and quantum system control. Combines system identification with receding-horizon optimization for robust quantum operations under noise and uncertainty.
Methodology for non-Markovian quantum systems under continuous measurement-based feedback using projection operator stochastic equations, where previously deterministic terms become stochastic ones depending on measurement records.
Q-DASC methodology for safe deployment of variational quantum circuit policies in physics-constrained control systems, with certified classical safety layers that handle model misspecification.
Hybrid quantum-classical architecture combining path signature kernels with QCNN for time series classification, addressing time reparameterization invariance. (arXiv: 2607.07634)
Quantum Convolutional Neural Network with Rough Path Signature Kernels for time series classification. Hybrid quantum-classical architecture using path signatures to handle time reparameterization invariance.
QAccCert methodology — hybrid quantum certification framework using FPGA + AI for entanglement verification via CHSH inequality. Applicable to quantum software engineering (QSE), NISQ hardware certification, and LLM-guided quantum parameter optimization.…
Quantum linear system algorithms with complexity independent of condition number - truncation-based and filtering-based solvers beyond the HHL kappa-barrier
Structured monitoring framework for quantum networks with standardized performance metrics including quality (entanglement fidelity, QBER), throughput/latency (entanglement rate, waiting time), timing (coincidence window, jitter), and exogenous factors…
Quantum network performance metrics, architecture design, and systems engineering patterns for distributed quantum computing. Covers entanglement distribution, error modeling, and network reliability analysis. Activation: quantum network, quantum internet,…
Quantum entanglement degree as novel PET biomarkers for tissue hypoxia detection. Based on first-in-human quantum entanglement PET imaging (J-PET scanner). Covers two quantum sensing methods: (1) ortho-positronium decay rate correlation with oxygen…