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Claude Skills by hiyenwong
github.com/hiyenwong9,934 skills5 installs19,223 views
- Scalable Memristivefriendly Reservoir Computing Time Seriesdynamics memristive reservoir computing methodology from arXiv:2604.19343. Memristive devices present a promising foundation for next-generation information processing by combining memory and computation within a single physi... Activation: dynamics, memristive, reservoir computingVotes: 0GitHub stars: 3
- Score Matching Gradient DecompositionGeometric decomposition of score matching errors in diffusion models using Helmholtz-Hodge decomposition. Proves that only gradient components affect marginal distribution quality, while solenoidal components are structurally invisible to Fokker-Planck dynamics.Votes: 0GitHub stars: 3
- Self Adaptive Anomaly Detection Rl Human Feedback VehiclesOnline anomaly detection framework for connected vehicles integrating factorized deep Q-network with self-attention, statistical drift detectors, and human-in-the-loop retraining. F1 score 0.69 vs 0.11 for single detectors, with sustained adaptation after concept drift. Use when working with anomaly-detection, reinforcement-learning, connected-vehicles.Votes: 0GitHub stars: 3
- Spatiotemporal Dynamical ComputationSkill for AI agent capabilitiesVotes: 0GitHub stars: 3
- Spatiotemporal Neural Coherence时空神经一致性解码方法论。使用 EEG 和光流特征构建预测性神经动力学的时空表征。适用于视觉语言处理的神经解码、预测推理分析。触发词：神经解码、预测推理、视觉语言、EEG 分析、光流特征、neural decoding、predictive inference、visual language。Votes: 0GitHub stars: 3
- Spatiotemporal TdannSpatiotemporal Topographic Deep Artificial Neural Network for modeling dorsal stream visual cortex. Uses 3D ResNet with MoCo self-supervised learning on naturalistic videos plus spatial loss to generate brain-like direction maps and pinwheel structures. Use when: modeling MT area, direction selectivity, dorsal stream organization, cortical self-organization, TDANN research.Votes: 0GitHub stars: 3
- Stability Of Flow Models For Graph SignalsGenerating 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.Votes: 0GitHub stars: 3
- State Space Ntk Collapse BifurcationsLocal theory of gradient descent near bifurcations via state-space neural tangent kernel (sNTK). Bifurcations collapse sNTK to rank-one operators corresponding to classical normal forms, funneling gradient descent into critical dynamical directions. Use when: analyzing RNN learning dynamics near bifurcations, studying NTK collapse, understanding gradient-based training of recurrent systems, bifurcation analysis in deep learning, neural tangent kernel for temporal tasks, normal form learning t...Votes: 0GitHub stars: 3
- Syndrome Adaptive Gain ControlSyndrome Adaptive Gain Control methodology for quantum LDPC error correction decoding. Adapts message gain during iterative decoding based on syndrome patterns.Votes: 0GitHub stars: 3
- Unified Control Theoretic Framework Saddle Point DynamicsThis paper studies equality-constrained minimization problems through the lens of feedback control. We introduce a unified control-theoretic framework by showing that a PID feedback law acting on the ... Activation: saddle-point dynamics, constrained optimization, primal-dual.Votes: 0GitHub stars: 3
- Unified Saddle Point ControlUnified control-theoretic framework for saddle-point dynamics in constrained optimization. PID saddle-point flow (PID-SPF) for equality-constrained minimization using feedback control principles. Activation: saddle-point dynamics, constrained optimization, primal-dual methods, control-theoretic optimization, augmented Lagrangian.Votes: 0GitHub stars: 3
- Single Entity Spiking Neuron ModelsComprehensive survey of single-entity spiking neuron models — classification of biologically plausible neural systems including discrete and continuous analogs, membrane potential dynamics, and components affecting neural dynamics for accurate simulation of biological processes.Votes: 0GitHub stars: 3
- Smm Transformer Spiking MultimodalSMM Transformer methodology leveraging Spiking Neural Networks (SNNs) for multimodal tasks by integrating spiking mechanisms into transformer architectures to achieve energy efficiency while maintaining performance across diverse modalities.Votes: 0GitHub stars: 3
- Snn Elephant ReinforcementSpiking Neural Networks with Elephant Reinforcement — finite stochastic SNN with memory-dependent threshold that modifies future excitability based on past firing activity.Votes: 0GitHub stars: 3
- Ai Systems Engineering V ModelExtended V-Model methodology for developing AI-enabled complex systems. Addresses the challenges of integrating AI into classical systems engineering processes with iterative development, continuous V&V, data management, safety by design, and DevOps integration. Activation: V-model AI systems, complex systems engineering, cognitive cyber-physical systems, AI system development lifecycle.Votes: 0GitHub stars: 3
- Arxiv 2608 05863v1 Runtime Observability For Heterogeneous Attention**arXiv ID:** 2608.05863v1 **Authors:** Fanzhe Wei, Li Liu, Ziyang Wang, Chenyu Wang **URL:** http://arxiv.org/abs/2608.05863v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 05944v1 Operating Multi Node Full Fine Tuning On Nvidia B3**arXiv ID:** 2608.05944v1 **Authors:** Seon Ho Kim, Ui Jeong Jeon, Su Hyeon Kim, Min Tae Hwang **URL:** http://arxiv.org/abs/2608.05944v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 06262v1 Hypothesis Testing With Conditional Queries Learna**arXiv ID:** 2608.06262v1 **Authors:** Zonghuan Xu **URL:** http://arxiv.org/abs/2608.06262v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 12072v1 Testing The Limits Of Past Adapted Explanations By**arXiv ID:** 2608.12072v1 **Authors:** George Sopasakis, Alexandros Sopasakis **URL:** http://arxiv.org/abs/2608.12072v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 12831v1 Fast A B N Testing Exact Multi Policy Comparison V**arXiv ID:** 2608.12831v1 **Authors:** Yuxiao Wen **URL:** http://arxiv.org/abs/2608.12831v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 13296v1 Large Scale Testing Global Optimization Methods Wi**arXiv ID:** 2608.13296v1 **Authors:** Wojciech Zarzecki, Jarosław Arabas **URL:** http://arxiv.org/abs/2608.13296v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 13438v1 Contactguard Pre Contact Execution Monitoring With**arXiv ID:** 2608.13438v1 **Authors:** Gehan Zheng, Matthew Johnson-Roberson, Weiming Zhi **URL:** http://arxiv.org/abs/2608.13438v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 18900v1 \Textsc Testifai Tomography Based Testing For Deep**arXiv ID:** 2608.18900v1 **Authors:** Arooj Arif, Tobias Hartung, Elena Botoeva, Alexandros Koliousis **URL:** http://arxiv.org/abs/2608.18900v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 23205v1 Cognitive Profiling Of Lrms Reasoning Traces Using**arXiv ID:** 2608.23205v1 **Authors:** Maria-Eleni Zoumpoulidi, Georgios Paraskevopoulos, Alexandros Potamianos **URL:** http://arxiv.org/abs/2608.23205v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 23955v1 Trust But Verify Rigorously Profiling Best Effort**arXiv ID:** 2608.23955v1 **Authors:** Matthew Andres Moreno, Santiago Rodriguez Papa, Charles Ofria, Luis Zaman, Emily Dolson **URL:** http://arxiv.org/abs/2608.23955v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 25920v1 Repair Or Resample Rethinking Failure Debugging In**arXiv ID:** 2608.25920v1 **Authors:** Zhongwen Luan, Xiaoyu Zhang, Ming Hu, Yue Yang, Jiongchi Yu, Xiaohong Chen **URL:** http://arxiv.org/abs/2608.25920v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 26899v1 Counterfactual Bias Testing For Application Tracki**arXiv ID:** 2608.26899v1 **Authors:** Sai Yashwant, Shruti Bansal, Anurag Dubey, Samaroha Chatterjee, Satyam Kumar, Shreyash Gupta, Gantala Thulsiram **URL:** http://arxiv.org/abs/2608.26899v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 30804v1 Geometric Attractor Monitoring A Robust And Frugal**arXiv ID:** 2608.30804v1 **Authors:** Martin Bonsergent-Brachet, Jesse Read, Dany Abboud **URL:** http://arxiv.org/abs/2608.30804v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 30916v1 Selection Aware Stress Testing For Interactive Age**arXiv ID:** 2608.30916v1 **Authors:** Yang Xu, Chenang Li, Jiefu Zhang, Haixiang Sun, Zhou Li, Vaneet Aggarwal **URL:** http://arxiv.org/abs/2608.30916v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2608 31105v1 Bloom Wilt Logit Tilting For Behaviour Elicitation**arXiv ID:** 2608.31105v1 **Authors:** Adrians Skapars, Edoardo Manino **URL:** http://arxiv.org/abs/2608.31105v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08463v1 Inclusive Electron Nucleus Cross Section Models Fr**arXiv ID:** 2609.08463v1 **Authors:** Krzysztof M. Graczyk, Beata E. Kowal, Rwik Dharmapal Banerjee, Jose Luis Bonilla, Hemant Prasad, Jan T. Sobczyk **URL:** http://arxiv.org/abs/2609.08463v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 08685v1 Hope Heterophily Aware Open Set Node Classificatio**arXiv ID:** 2609.08685v1 **Authors:** Yumeng Dai, Yue Tan, Yixin Liu, Chenxu Wang, Pinghui Wang, Tao Qin **URL:** http://arxiv.org/abs/2609.08685v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10125v1 Sa Profile Automated Sulcus Angle Profiling From S**arXiv ID:** 2609.10125v1 **Authors:** Michael Wehrli, Leo Widmer, Edwin Li, Noel Fiechter, Lorenzo Pettinari, Sidaty El Hadramy, Carol C. Hasler, Philippe C. Cattin **URL:** http://arxiv.org/abs/2609.10125v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Catbench A Compiler Autotuning Benchmarking Suite For Blackbox Optimization**arXiv ID:** 2406.17811 **Authors:** Jacob O. Tørring, Carl Hvarfner, Luigi Nardi, Magnus Själander **Published:** 2024-06-24T20:15:04Z **Abstract:** Bayesian optimization is a powerful method for automating tuning of compilers. The complex landscape of autotuning provides a myriad of rarely considered structural challenges for black-box optimizers, and the lack of standardized benchmarks has limited the study of Bayesian optimization within the domain. To address this, we present CATBench, ...Votes: 0GitHub stars: 3
- Data Poisoning Informativity ObservabilityData poisoning attacks against informativity-based analysis for observability in data-driven control systems. Invariance-based attack synthesis using invertible linear transformations. Activation: data poisoning, cyber attack control, observability attack, informativity analysis attack.Votes: 0GitHub stars: 3
- Github AuthSet up GitHub authentication for the agent using git (universally available) or the gh CLI. Covers HTTPS tokens, SSH keys, credential helpers, and gh auth — with a detection flow to pick the right method automatically.Votes: 0GitHub stars: 3
- Github Code ReviewReview code changes by analyzing git diffs, leaving inline comments on PRs, and performing thorough pre-push review. Works with gh CLI or falls back to git + GitHub REST API via curl.Votes: 0GitHub stars: 3
- Github IssuesCreate, manage, triage, and close GitHub issues. Search existing issues, add labels, assign people, and link to PRs. Works with gh CLI or falls back to git + GitHub REST API via curl.Votes: 0GitHub stars: 3
- Github Pr WorkflowFull pull request lifecycle — create branches, commit changes, open PRs, monitor CI status, auto-fix failures, and merge. Works with gh CLI or falls back to git + GitHub REST API via curl.Votes: 0GitHub stars: 3
- Github Repo ManagementClone, create, fork, configure, and manage GitHub repositories. Manage remotes, secrets, releases, and workflows. Works with gh CLI or falls back to git + GitHub REST API via curl.Votes: 0GitHub stars: 3
- Karma Mechanisms Decentralised CooperativeMulti-Agent Path Finding (MAPF) is a fundamental coordination problem in large-scale robotic and cyber-physical systems, where multiple agents must compute conflict-free trajectori... Activation: multi-agentVotes: 0GitHub stars: 3
- Karma Mechanisms MapfKarma Mechanisms for Decentralised Cooperative Multi-Agent Path Finding (MAPF). Novel coordination framework using artificial non-tradeable credits (Karma) to account for past cooperative behavior and regulate conflict resolution. Bilateral negotiation enables pairwise replanning without global priority structures. Promotes long-term fairness under limited communication. Use for: (1) Decentralized multi-agent coordination, (2) fair resource allocation, (3) path planning without centralization...Votes: 0GitHub stars: 3
- Microservices Auto RemediationMicroservices Auto-Remediation - Experience-Simulation Reinforcement Fine-Tuning (ES-RFT) combining historical incident library, failure simulation, and RL-based policy optimization... Activation: microservices remediation, auto-remediation, SRE.Votes: 0GitHub stars: 3
- Model Callers For Transforming Predictive And Generative Ai Applications**arXiv ID:** 2406.15377 **Authors:** Mukesh Dalal **Published:** 2024-04-17T12:21:06Z **Abstract:** We introduce a novel software abstraction termed "model caller," acting as an intermediary for AI and ML model calling, advocating its transformative utility beyond existing model-serving frameworks. This abstraction offers multiple advantages: enhanced accuracy and reduced latency in model predictions, superior monitoring and observability of models, more streamlined AI system architectures, ...Votes: 0GitHub stars: 3
- Optimal Stabilizer Testing Limited MemoryStabilizer state testing and learning under limited quantum memory constraints - sample complexity bounds for testing and learning with k-qubit memory.Votes: 0GitHub stars: 3
- Page Prototypebased Modellevel Explanations For Graph Neural Networks**arXiv ID:** 2210.17159 **Authors:** Yong-Min Shin, Sun-Woo Kim, Won-Yong Shin **Published:** 2022-10-31T09:10:06Z **Abstract:** Aside from graph neural networks (GNNs) attracting significant attention as a powerful framework revolutionizing graph representation learning, there has been an increasing demand for explaining GNN models. Although various explanation methods for GNNs have been developed, most studies have focused on instance-level explanations, which produce explanations tailored...Votes: 0GitHub stars: 3
- Qlass Serverless Entangled SchedulerEFaaS (Entangled Functions as a Service) methodology for quantum-classical serverless scheduling of hybrid variational algorithms. Enables efficient orchestration of quantum circuit evaluations within serverless compute frameworks, optimizing classical-quantum communication patterns for hybrid variational workloads. Use when: designing hybrid quantum-classical systems, optimizing variational algorithm execution, building quantum serverless platforms, scheduling quantum-classical workloads, or...Votes: 0GitHub stars: 3
- Requesting Code ReviewPre-commit verification pipeline — static security scan, baseline-aware quality gates, independent reviewer subagent, and auto-fix loop. Use after code changes and before committing, pushing, or opening a PR.Votes: 0GitHub stars: 3
- Scaling Kubernetes To 2500 NodesSkill for AI agent capabilitiesVotes: 0GitHub stars: 3
- Scaling Kubernetes To 7500 NodesSkill for AI agent capabilitiesVotes: 0GitHub stars: 3