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Claude Skills by hiyenwong
github.com/hiyenwong9,934 skills5 installs19,223 views
- Experimental Quantum Key Distribution Indefinite Causal OrderA skill for understanding and applying the methods from the arXiv paper: Experimental Quantum Key Distribution in an Indefinite Causal Order (arXiv: 2608.13561v1)Votes: 0GitHub stars: 3
- Expert Analysis Evaluation Quantum PortfolioExpert Analysis Evaluation framework bridging computational optimization and practical viability in quantum portfolio optimization. Financial professionals assess economic soundness and market feasibility of quantum-optimized portfolios beyond algorithmic metrics. Based on arXiv:2507.20532v1.Votes: 0GitHub stars: 3
- Explainable Gnn Eeg NeurologicalExplainable GNN for EEG Neurological EvaluationVotes: 0GitHub stars: 3
- Explicit Operator Neural ComputationMathematical correspondence between state space models (SSMs) and exactly solvable nonlinear oscillator networks. Bridges modern neural architectures with theoretical physics models for understanding end-to-end neural computation.Votes: 0GitHub stars: 3
- Exploiting Symmetry Quantum Reservoir ComputingExploiting Symmetry in Quantum Reservoir Computing (QRC) methodology — observable-orbit completion aligns encoding, dynamics, measurement, and readout so symmetry-induced inductive bias is visible in the measured feature map; validated on spin-ring, real-weather cyclic forecasting, and IBM hardware.Votes: 0GitHub stars: 3
- Exploratory Predictive Representation Geometry探索性行为塑造预测性表征几何的方法论。通过主动感知框架研究探索-利用平衡如何影响内部表征组织。探索性行为使表征更具空间结构性，更好地保留迷宫转换结构。激活词：探索性学习、exploratory behavior、predictive coding、predictive representations、active sensing、latent space geometry、行为-学习循环。Votes: 0GitHub stars: 3
- Extended Predictive Coding Exponential FamilyExtended Predictive Coding framework using exponential-family distributions for variational free-energy minimization. Captures biological network properties: nonlinearity, heterogeneity, positive firing rates. Biologically plausible local plasticity rules. Activation: predictive coding, exponential family, free-energy principle, variational inference, local plasticity, 预测编码, 自由能原理.Votes: 0GitHub stars: 3
- Extreme Quantum CognitionExtreme Quantum Cognition Machines (EQCM) — quantum learning architectures for deliberative decision making tolerant to noisy and contradictory training data. Combines quantum extreme learning, quantum reservoir computing, and dynamical attention mechanisms for symbolic inference, sequence analysis, anomaly detection. Use when: quantum cognition architectures, deliberative decision making with noisy data, quantum reservoir computing, quantum extreme learning machines, dynamical attention in q...Votes: 0GitHub stars: 3
- Eyebrain Lateralization PupilEyeBrain methodology for classifying left and right brain lateralization activity using pupil diameter and fixation duration. Non-invasive cognitive state detection via eye-tracking. Triggers: eyebrain, brain lateralization, pupil diameter, fixation duration, eye-tracking, cognitive load.Votes: 0GitHub stars: 3
- Face Perception Inverse GenerativeHuman face perception methodology using controversial stimulus pairs to distinguish between theoretically distinct DNN models. Shows that human face perception is shaped by inverse-generative mechanisms that infer latent causes of facial appearance and discount nuisance variation, tuned by natural image statistics. arXiv:2605.12619.Votes: 0GitHub stars: 3
- Families Linear AlgebraFramework for Advanced (Multi)Linear Infrastructure in Engineering and Science. Dense linear algebra and tensor operations framework extending BLAS/LAPACK. Use when: linear algebra library design, BLAS implementation, LAPACK algorithms, tensor operations, high-performance computing, dense matrix operations, scientific computing infrastructure, GPU-accelerated linear algebra, or multi-node/multi-GPU dense algebra.Votes: 0GitHub stars: 3
- Fase Semantic Entropy CodeFast Adaptive Semantic Entropy (FASE) methodology for quantifying uncertainty in multi-agent code generation. Approximates functional correctness via minimum spanning tree of structural and semantic dissimilarity graphs, achieving 25% improvement in Spearman correlation and 19% increase in ROCAUC over LLM-driven semantic entropy, at ~0.3% of the computational cost. Activation: semantic entropy, code uncertainty, multi-agent code quality, FASE, functional correctness estimation.Votes: 0GitHub stars: 3
- Fast Efficient Coding CriticalityFast efficient coding and sensory adaptation in gain-adaptive recurrent networks. Theoretical framework showing gain modulation in recurrent circuits reconciles adapter-repulsion and prior-attraction under a unified efficient-coding objective.Votes: 0GitHub stars: 3
- Fault Tolerant Ancilla Preparation BchEfficient fault-tolerant ancilla preparation for quantum BCH codes via cyclic symmetry. Two-stage approach using non-fault-tolerant preparation + entanglement distillation with cyclic symmetry exploitation. arXiv: 2605.19471.Votes: 0GitHub stars: 3
- Fc Guided Band Selection BciFunctional Connectivity-guided spectral band selection for Motor Imagery Brain-Computer Interfaces (MI-BCIs). Ranks frequency bands using phase-based connectivity (wPLI, PLV, PLI) across sensorimotor channels to identify subject-specific discriminative bands, reducing CSP pipeline dimensionality while maintaining classification accuracy.Votes: 0GitHub stars: 3
- Fc Guided Band Selection Mi BciFunctional connectivity-guided spectral band selection for motor imagery BCI. Uses phase-based connectivity (wPLI, PLV, PLI) to identify optimal EEG frequency bands for CSP-based decoding instead of heuristic filter banks. Activation: BCI band selection, motor imagery, functional connectivity CSP, FC-guided BCI, spectral band optimization, EEG feature selection.Votes: 0GitHub stars: 3
- Fcn Llm Brain Network UnderstandingIntegrating LLMs with functional connectivity networks for brain analysis. Activation: LLM-brain integration, functional connectivity, graph-text alignment.Votes: 0GitHub stars: 3
- Fdnml Cognitive Fatigue DetectionFractional Dynamical Networks-based Machine Learning (FDNML) for EEG cognitive fatigue detection using coupled fractional-order differential equations, multifractal analysis, and Wasserstein distance metrics. Activation: cognitive fatigue, fractional dynamics, EEG fatigue, non-Markovian brain modeling, multifractal analysis, state transition detection.Votes: 0GitHub stars: 3
- Feature Visualization Brain EncoderFeature visualization as interpretability technique for brain encoder models. Uses gradient ascent on predicted activation for target ROIs to qualitatively evaluate whether encoders have internalized functional brain organization. Activation: feature visualization brain encoder, cortical selectivity validation, brain encoder interpretability, ROI feature visualization.Votes: 0GitHub stars: 3
- Feddose Federated Brain ConnectivityFedDOSE federated brain dFC with site decomposition.Votes: 0GitHub stars: 3
- Feddose Federated Learning Dynamic Functional ConnectivityFedDOSE framework for federated learning that explicitly decomposes site effects for modeling brain dynamic functional connectivity. Introduces Modularity-Guided Tucker Decomposition to encode high-dimensional dFC tensors and capture modular-level spatio-temporal patterns. Uses class-specific prototypes with Optimal Transport barycenter formulation and Procrustes analysis for global alignment across sites.Votes: 0GitHub stars: 3
- Federated Brain Trajectory Gnn联邦多轨迹图神经网络预测婴儿脑连接演化。FedGmTE-Net++框架，支持多模态/多轨迹预测，在数据稀缺环境下聚合多家医院的学习，保护数据隐私。包含辅助正则化和两步插补策略。触发词：婴儿脑发育、脑连接预测、联邦学习、图神经网络、多轨迹预测、数据稀缺、infant brain、federated learning、trajectory prediction、GNN。Votes: 0GitHub stars: 3
- Federated Cognitive Digital Twins Edge CloudFederated Cognitive Digital Twin (FCDT) architecture methodology combining federation and cognition within a unified approach for distributed Cyber-Physical Systems (CPSs).Votes: 0GitHub stars: 3
- Federated Quantum Medical DiagnosisFederated Quantum Neural Network methodology for privacy-preserving medical image diagnosis. Combines federated learning with quantum neural networks for distributed medical imaging analysis without sharing raw patient data. Use when: federated quantum learning, privacy-preserving medical AI, distributed quantum ML for healthcare, FQPDR pattern.Votes: 0GitHub stars: 3
- Federated Quantum MedicalFederated quantum learning methodology for privacy-preserving medical diagnosis. Combines federated learning (FL) with quantum neural networks (QNN) for early disease detection without sharing sensitive patient data across institutions. Use when: building privacy-preserving medical AI, federated quantum learning, cross-institutional medical data collaboration, early disease detection with quantum models, diabetic retinopathy detection, medical image privacy, FQPDR methodology, quantum federat...Votes: 0GitHub stars: 3
- Fermi Dirac Quantized NeuronsFermi-Dirac quantization methodology for neural networks — reinterprets classical neurons as parameterized Hamiltonians and replaces variables with quantum operators. BQP-complete for certain decision problems. Use when: designing quantum neural architectures, quantizing activation functions (ReLU, GeLU, sigmoid), building hybrid quantum-classical neural algorithms, analyzing quantum advantage in neural computation, or studying the quantum-classical boundary in machine learning.Votes: 0GitHub stars: 3
- Fermionic Quantum ProcessorProgrammable fermionic quantum processors with globally controlled lattices. Universal fermionic quantum processing framework for neutral atoms in optical lattices, supporting Fermi-Hubbard type models with time-dependent control over tunneling and interaction. Keywords: fermionic quantum processing, neutral atoms, optical lattice, Fermi-Hubbard model, universal quantum computation, global control, hybrid analog-digital.Votes: 0GitHub stars: 3
- Ferroelectric Snn EegPersonalized Spiking Neural Networks with Ferroelectric Synapses for EEG Signal Processing. Covers deployment of SNNs on ferroelectric memristive hardware for adaptive EEG-based motor imagery decoding, mixed-precision training with device-aware updates, and subject-specific transfer learning on neuromorphic platforms. Use when working with: ferroelectric synapses, memristive SNN deployment, EEG-based BCI personalization, neuromorphic hardware constraints, mixed-precision spiking training, or ...Votes: 0GitHub stars: 3
- FinanceEmpirical investigation of long-range dependence (LRD) in financial markets and evaluation of deep generative models' ability to reproduce such temporal structures across equity, commodity, and energy sectors.Votes: 0GitHub stars: 3
- A Significantly Better Class Of Activation Functions Than Relu Like Activation Functions**arXiv ID:** 2405.04459 **Authors:** Mathew Mithra Noel, Yug Oswal **Published:** 2024-05-07T16:24:03Z **Abstract:** This paper introduces a significantly better class of activation functions than the almost universally used ReLU like and Sigmoidal class of activation functions. Two new activation functions referred to as the Cone and Parabolic-Cone that differ drastically from popular activation functions and significantly outperform these on the CIFAR-10 and Imagenette benchmmarks are prop...Votes: 0GitHub stars: 3
- Adaptive Perturbationbased Gradient Estimation For Discrete Latent Variable Models**arXiv ID:** 2209.04862 **Authors:** Pasquale Minervini, Luca Franceschi, Mathias Niepert **Published:** 2022-09-11T13:32:39Z **Abstract:** The integration of discrete algorithmic components in deep learning architectures has numerous applications. Recently, Implicit Maximum Likelihood Estimation (IMLE, Niepert, Minervini, and Franceschi 2021), a class of gradient estimators for discrete exponential family distributions, was proposed by combining implicit differentiation through perturbation...Votes: 0GitHub stars: 3
- Arxiv 2608 05255 An Emerging Retail Portfolio Management ApplicatioAn Emerging Retail Portfolio Management Application: Personalized, Tax-Aware Reinforcement Learning with Natural Language Goals (arXiv: 2608.05255)Votes: 0GitHub stars: 3
- Arxiv 2608 05373 Velocity And Regime Aware Detection Of Intraday OpVelocity- and Regime-Aware Detection of Intraday Options Market Manipulation, with Explainable Attribution (arXiv: 2608.05373)Votes: 0GitHub stars: 3
- Arxiv 2608 06108 Evaluating Investment Logic In Large Language ModeEvaluating Investment Logic in Large Language Models: A Real-World Benchmark Towards Personalzied Financial Agents (arXiv: 2608.06108)Votes: 0GitHub stars: 3
- Arxiv 2608 06108v1 Evaluating Investment Logic In Large Language Mode**arXiv ID:** 2608.06108v1 **Authors:** Yuanhong Jiang, Jingjie Zou, Zhenghong Lin, Xusheng Yu, Qiqi Huang, Shuai Jia, Shijie Dai **URL:** http://arxiv.org/abs/2608.06108v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 13082v1 Lob Id Evaluating Synthetic Market Data By Incepti**arXiv ID:** 2608.13082v1 **Authors:** Andreea Bacalum, Zhuohan Wang, Ollie Olby, Martin Garaj, Namid Stillman **URL:** http://arxiv.org/abs/2608.13082v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 18911v1 Converting Expert Deliberation Into Financial Sign**arXiv ID:** 2608.18911v1 **Authors:** Vivek Batra, Kristin Chen, Sanjiv Das, Samuel Judge, Harshad Khadilkar, Sukrit Mittal, Amir Nasrollahzadeh, Daniel Ostrov, Jacob Sisk **URL:** http://arxiv.org/abs/2608.18911v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 23393v1 Kellyboost Growth Optimal Portfolio Construction W**arXiv ID:** 2608.23393v1 **Authors:** Jiayu Li **URL:** http://arxiv.org/abs/2608.23393v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 26526v1 High Probability Derivative Bounds For Random Tanh**arXiv ID:** 2608.26526v1 **Authors:** Josef Dick, Michael Feischl, Fabian Zehetgruber **URL:** http://arxiv.org/abs/2608.26526v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 02646v1 Differentiable Electricity Market Clearing For Gra**arXiv ID:** 2609.02646v1 **Authors:** Luca Mungo, Maarten P. Scholl, Arnau Quera-Bofarull **URL:** http://arxiv.org/abs/2609.02646v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Bbqram State Preparation FinanceArchitecture-aware quantum state preparation using Bucket Brigade QRAM (BBQRAM) with segment tree for polylogarithmic query time. Covers complex-valued matrix encoding, classical precomputation of rotation angles, and magnitude-then-phase procedures. Enables efficient data loading for quantum finance applications. Based on arXiv:2604.25644. Use when: designing QRAM-based quantum data loaders, optimizing state preparation for quantum finance, loading complex-valued financial data into quantum ...Votes: 0GitHub stars: 3
- Comparative Analysis Of Neural Network Architectures For Shortterm Forex Forecasting**arXiv ID:** 2405.08045 **Authors:** Theodoros Zafeiriou, Dimitris Kalles **Published:** 2024-05-13T14:51:02Z **Abstract:** The present document delineates the analysis, design, implementation, and benchmarking of various neural network architectures within a short-term frequency prediction system for the foreign exchange market (FOREX). Our aim is to simulate the judgment of the human expert (technical analyst) using a system that responds promptly to changes in market conditions, thus enab...Votes: 0GitHub stars: 3
- Currency Exchange Prediction Using Machine Learning Genetic Algorithms And Technical Analysis**arXiv ID:** 1805.11232 **Authors:** Gonçalo Abreu, Rui Neves, Nuno Horta **Published:** 2018-05-29T03:36:34Z **Abstract:** Technical analysis is used to discover investment opportunities. To test this hypothesis we propose an hybrid system using machine learning techniques together with genetic algorithms. Using technical analysis there are more ways to represent a currency exchange time series than the ones it is possible to test computationally, i.e., it is unfeasible to search the whole ...Votes: 0GitHub stars: 3
- Dealer Market Competition Nash EquilibriumVariational approach to modeling dealer market competition with internalisation and externalisation — closed-form Nash equilibrium for multi-dealer order flow competition with inventory risk management.Votes: 0GitHub stars: 3
- Decomposing Financial Market Dynamics Via MechanisDerived from arXiv:2606.23158 - Decomposing Financial Market Dynamics via Mechanism Analysis in an Evolutionary Multi-Agent SimulationVotes: 0GitHub stars: 3
- Derivative Informed Operator Learning FinanceDerivative-informed operator learning framework for financial decision systems — matching pricing operators and Fréchet derivatives to reduce hedging error (Vega -40%, Delta -15%).Votes: 0GitHub stars: 3
- Distributional Portfolio OptimizationDistributional Portfolio Optimization (DPO) unified framework — organizing Bayesian, robust, chance-constrained, stochastic-allocation, and distributional RL portfolio methods through joint coupling Gamma_theta(dw,dr). Includes Wasserstein-CVaR duality, credible-radius calibration, and distributional Bellman contraction. Activation: distributional portfolio optimization, DPO, Wasserstein DRO, Bayesian portfolio, CVaR, credible radius, distributional reinforcement learning.Votes: 0GitHub stars: 3
- Eco3s Complex Socio Economic System Simulation ViaEco3S: Complex Socio-Economic System Simulation via Agent-Based ModelsVotes: 0GitHub stars: 3
- Esg Joint Fragility Equity MarketsFramework for analyzing ESG's association with joint fragility in equity markets — clustered downside risk across losses, volatility spikes, and illiquidity using cofragility state detection.Votes: 0GitHub stars: 3
- Input Specific Neural Networks**arXiv ID:** 2503.00268 **Authors:** Asghar A. Jadoon, D. Thomas Seidl, Reese E. Jones, Jan N. Fuhg **Published:** 2025-03-01T00:57:16Z **Abstract:** The black-box nature of neural networks limits the ability to encode or impose specific structural relationships between inputs and outputs. While various studies have introduced architectures that ensure the network's output adheres to a particular form in relation to certain inputs, the majority of these approaches impose constraints on only ...Votes: 0GitHub stars: 3