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Claude Skills by hiyenwong
github.com/hiyenwong9,934 skills5 installs19,223 views
- Ember Hybrid Snn Llm Cognitive ArchitectureEMBER hybrid cognitive architecture combining LLM reasoning with persistent biologically-grounded SNN memory substrate. Autonomous cognitive behavior via STDP-based lateral propagation.Votes: 0GitHub stars: 3
- Ember Snn Llm Cognitive ArchitectureHybrid LLM-SNN cognitive architecture that reorganizes the LLM-memory relationship by placing the LLM as a replaceable reasoning engine within a persistent, biologically-grounded SNN associative substrate. Features experience-modulated dynamics and emergent autonomous reasoning capabilities. Activation: EMBER architecture, hybrid LLM SNN, experience-modulated reasoning, associative memory substrate, cognitive architecture, spiking neural network memory, autonomous cognitive behaviour, emergen...Votes: 0GitHub stars: 3
- Embodied Neurocomputation FrameworkEmbodied Neurocomputation framework for interfacing biological neural cultures with scaled task-driven validation. Systems-level approach to multi-variable optimization of encoding/decoding between silicon computing and living biology. Demonstrates that biological neural networks (BNNs) can outperform DQN agents in goal-driven navigation when encoding parameters are properly optimized.Votes: 0GitHub stars: 3
- Embodied NeurocomputationEmbodied Neurocomputation framework for interfacing biological neural cultures (BNNs) with task-driven validation. Addresses the encoding/decoding optimization problem between silicon computing and living biological neural networks. Demonstrates first large-scale parameter optimization of BNN agents performing closed-loop navigation, evaluating ~1,300 configurations over 4,000+ hours of agent-environment interactions. BNN configurations outperform silicon-based DQN agents under same interacti...Votes: 0GitHub stars: 3
- Embodied Vr Feedback 3d Motor Imagery BciEmbodied Virtual Reality feedback reshapes neural representations to support continuous 3D motor imagery decoding in brain-computer interfaces. First systematic investigation of embodied VR feedback during real-time 3D virtual limb control. Use when: (1) Designing VR-based BCI systems, (2) Studying motor imagery neural representations, (3) Comparing VR vs screen feedback modalities, (4) Investigating longitudinal BCI training effects. Activation: embodied VR feedback, motor imagery BCI, 3D vi...Votes: 0GitHub stars: 3
- Embodied Vr Feedback Reshapes Neural RepresentationsEmbodied Virtual Reality feedback methodology for continuous 3D motor imagery BCI decoding. First systematic investigation showing VR feedback elicits more decodable and generalizable neural representations than screen feedback. CNN-LSTM decoder achieves r=0.762 under VR vs r=0.672 screen. Use when: (1) Designing continuous BCIs for intuitive motor control, (2) Implementing VR-based neurorehabilitation systems, (3) Studying neural representation generalization across feedback modalities, (4) ...Votes: 0GitHub stars: 3
- Emergent Generalization Representation LearningEmergent generalization by representation learning in artificial neural networks. An explicit information bottleneck forcing an RNN to learn a low-dimensional representation is necessary for rotational and out-of-distribution generalization in time-series prediction. Uses information-theoretic causal emergence to characterize the memorization-to-generalization transition (non-monotonic down-min-up trajectory) and finds analogous dynamics in CA1 hippocampal activity of mice learning an alterna...Votes: 0GitHub stars: 3
- Emergent Language Consciousness涌现语言方法论 — 使用多智能体强化学习中的涌现语言作为研究意识的生成工具。从最小先验出发，通过任务压力发展通信，确保涌现结构的因果可归因性。Votes: 0GitHub stars: 3
- Emergent Systems DesignEmergent Systems Design - 自动化工程设计具有涌现属性的复杂系统。核心技术：描述性统计转损失函数、梯度下降优化涌现特征、Kuramoto耦合振荡器测试床。激活词：emergent design, emergence engineering, 涌现设计, 复杂系统工程.Votes: 0GitHub stars: 3
- Emergent Topological Brain OrganoidsApply persistent homology to MEA recordings of spontaneous brain-organoid activity. Detects H1 loops and H2 voids in correlation networks, compares them to rate-preserving null models, and identifies non-redundant loop-carrying cores.Votes: 0GitHub stars: 3
- Emomind Affective Brain DecodingEnd-to-end pipeline for decoding affective captions directly from fMRI signals using continuous emotion vectors and classifier-free guidance rewriting. Use when: brain-to-text with emotion/affect, fMRI affective decoding, continuous emotion representation from brain signals, individualized affective caption generation, classifier-free guidance for neural decoding. Activation: emomind, affective brain decoding, emotion fMRI, brain-to-text emotion, affective caption, continuous emotion vector, ...Votes: 0GitHub stars: 3
- Emrformer Neuromorphic AmrEMRFormer: End-to-End Radar and Communication Modulation Recognition with Neuromorphic Computing using spike-driven transformers on KA200 neuromorphic chip. Achieves SOTA accuracy with 90%+ energy reduction. (arXiv: 2606.24075)Votes: 0GitHub stars: 3
- Energy Based Autoregressive Neural DynamicsEnergy-based Autoregressive Generation (EAG) framework for neural population dynamics using energy-based transformer in latent space with strictly proper scoring rules. Activation triggers: energy-based model, neural population dynamics, autoregressive generation, brain modeling, transformer dynamics.Votes: 0GitHub stars: 3
- Energy Based NeurocomputationEnergy-based dynamical systems framework for neurocomputation, learning, and optimization. Unifies Hopfield networks, Boltzmann machines, modern EBMs, and equilibrium propagation under a single energy landscape formulation. Covers gradient flow dynamics, attractor analysis, contrastive learning, and biologically-plausible learning rules. Activation: energy-based models, EBMs, neural dynamics, Hopfield networks, energy landscape, attractor dynamics, gradient flow, equilibrium propagation, cont...Votes: 0GitHub stars: 3
- Energy Regularized Neural MpcEnergy-based regularization for learning residual dynamics in Neural MPC for omnidirectional aerial robots. Use when: (1) Designing neural network dynamics models for physical systems, (2) Implementing Model Predictive Control with learned dynamics, (3) Building physics-informed neural networks for robotic control, (4) Ensuring physically plausible predictions in out-of-distribution scenarios. Activation: energy regularization, neural MPC, residual dynamics, aerial robots, energy-based learni...Votes: 0GitHub stars: 3
- Engineering Grounded Ai Power SystemsEngineering-Grounded AI (EGAI) framework for power systems education using hands-on executable modules that follow domain rules rather than acting as black boxes.Votes: 0GitHub stars: 3
- Ensemble Engineering QuantumEnsemble engineering methodology to overcome destructive cancellation in quantum measurements on NISQ devices. Addresses near-uniform ensemble sampling issues that render physically relevant expectation values unobservable. Activation: ensemble engineering, quantum measurement cancellation, NISQ observable estimation, destructive quantum cancellation, quantum sampling optimization.Votes: 0GitHub stars: 3
- Entropic Explanation Autism SamenessInformation theory-based framework explaining insistence on sameness in autism through entropy minimization. Uses metric D_H(R, M) = H(R|M) + H(M|R) to quantify surprise and uncertainty reduction strategies. Provides formal foundations for autism therapies, robotic caregivers, and computational models of cognitive limitations.Votes: 0GitHub stars: 3
- Entropic Time Psychophysics Deformed Neural DynamicsUnified physical theory linking entropy production, subjective time perception, and deformed neural dynamics. Derives conformable time operators from thermodynamic principles and predicts psychedelic time dilation and cognitive aging effects.Votes: 0GitHub stars: 3
- Entropy Brain Connectivity Paths使用熵测度识别脑连接路径的方法论。通过信息论工具（熵密度、有效测度复杂度、Lempel-Ziv距离）检测线性与非线性动态，无需预设参数或模型假设。适用于任务态fMRI分析、脑区连接发现、探索性研究。触发词：脑连接、熵测度、信息流、fMRI分析、非线性动态、brain connectivity、entropy、information flow、Lempel-Ziv。Votes: 0GitHub stars: 3
- Episodic Learning Neural NetworksInternally triggered retrospective learning paradigm for neural networks. Instead of continuous externally-driven weight updates, parameter modifications are governed by internally generated events from the network's own representational dynamics. Uses latent trace accumulation, internal predictive process, and adaptive discrepancy thresholding to trigger sparse, episodic learning events. Use when: designing energy-efficient learning systems, edge computing with limited compute, continual lea...Votes: 0GitHub stars: 3
- Eppo Entropy Pacing Multi Task RlEntropy Pacing Policy Optimization (EPPO) methodology for multi-task agentic RL. Coordinates entropy across tasks using dynamic clipping to prevent exploration-exploitation pace mismatch between tasks.Votes: 0GitHub stars: 3
- Equation Free Digital TwinsEquation-free digital twin framework using Koopman operator theory and Hankel-matrix embeddings for real-time structural state reconstruction without physical models. Use when: (1) building digital twins for complex engineering structures, (2) virtual sensing from partial observations, (3) Koopman-based system identification, (4) real-time monitoring of nonlinear structural dynamics.Votes: 0GitHub stars: 3
- Equilibrium Dynamics Sound LocalizationEquilibrium dynamics framework for microsecond-precision sound localization without explicit delay linesVotes: 0GitHub stars: 3
- Equilibrium Propagation Lif SnnEquilibrium Propagation (EP) with Predictive Learning in Leaky Integrate-and-Fire Spiking Neural Networks. Biologically plausible alternative to backpropagation for training SNNs using energy-based two-phase learning. Use when training SNNs without backpropagation through time, implementing biologically realistic learning rules, or applying equilibrium-based optimization to spiking neuron networks.Votes: 0GitHub stars: 3
- Equivariant Neural Belief PropagationEquivariant Neural Belief Propagation (ENBP) for SE(3)-symmetric probabilistic inference with Gaussian mixture messagesVotes: 0GitHub stars: 3
- Equivariant QaoaEquivariant QAOA methodology incorporating symmetry constraints into quantum approximate optimization. Uses group-theoretic structure to reduce parameter space and improve optimization efficiency for combinatorial problems with inherent symmetries. Use when solving symmetric optimization problems, reducing QAOA parameter space, or leveraging problem structure in quantum algorithms.Votes: 0GitHub stars: 3
- Equivariant Rl CliffordEquivariant reinforcement learning for Clifford quantum circuit synthesis. Use when synthesizing Clifford quantum circuits with RL, designing equivariant neural networks for quantum tasks, building size-agnostic policies across qubit counts, or optimizing quantum circuit compilation with all-to-all connectivity. Covers graph-based state representations, permutation-equivariant architectures, and RL reward design for gate synthesis. Activation: equivariant RL, quantum circuit synthesis, Cliffo...Votes: 0GitHub stars: 3
- Equivariant Rl Quantum Circuit SynthesisEquivariant reinforcement learning for Clifford quantum circuit synthesis. Use when designing RL-based quantum circuit synthesis, leveraging group symmetries in quantum operations, or building equivariant architectures for quantum computing tasks.Votes: 0GitHub stars: 3
- Era Entropy Token Pruning MllmERA (Entropy-guided Visual Token Pruning with Rectified Attention) for efficient Multimodal Large Language ModelsVotes: 0GitHub stars: 3
- Erecon Snn Nvcim HardwareE-ReCON energy- and resource-efficient precision-configurable sparse nvCIM macro for conventional and spiking neural edge inference. Activation: nvCIM, ReRAM CIM, SNN hardware accelerator, edge-AI hardware, compute-in-memory SNN, neuromorphic hardware macroVotes: 0GitHub stars: 3
- Errorless Irrationality Inverse Base Rate EffectUnified computational account of the inverse base-rate effect that persists across predictive, observational, and unsupervised learning procedures, proposing the OSCAR model based on self-generated feedback and pattern completion dynamics.Votes: 0GitHub stars: 3
- Ethics Ai Life Sciences Universality DiversityFramework for AI ethics in life sciences based on human brain architecture, global neuronal workspace, and reward cycles of wanting-liking-satiety rather than maximizationVotes: 0GitHub stars: 3
- Evaluating Encoding Strategies Biological Neural NetworksSkill for understanding and applying the research from arXiv:2607.13644 "Evaluating Encoding Strategies for Closed-Loop Classification in Biological Neural Networks"Votes: 0GitHub stars: 3
- Evaluation Resolution Confounds Rsa Visual CortexResolution confounds in RSA visual cortex comparisons.Votes: 0GitHub stars: 3
- Event Based Neural Decoding NeuroprostheticEvent-based neural decoding framework using spiking GRU with sparse graded spikes for efficient on-device motor control. Achieves >90% decoding accuracy with <1mW power consumption on neuromorphic hardware for neuroprosthetic applications.Votes: 0GitHub stars: 3
- Event Driven Eligibility PropagationEvent-driven eligibility propagation (e-prop) extension for large sparse recurrent spiking networks. Biologically plausible learning rule with continuous dynamics, strict locality, and sparse connectivity. Scales to millions of neurons without compromising performance. Integrates neuromorphic principles into AI learning algorithms. Keywords: e-prop, event-driven learning, eligibility trace, sparse SNN, biologically plausible, recurrent connectivity, neuromorphic MNIST, scalable learning, loca...Votes: 0GitHub stars: 3
- Event Driven Hopfield RetrievalEvent-driven asynchronous retrieval in high-capacity kernel Hopfield networks. KLR Hopfield networks achieve P/N ≈ 30 storage capacity with asynchronous updates, enabling energy-efficient neuromorphic deployment. Event count matches initial Hamming distance — minimal spurious oscillations. Activation: Hopfield network, kernel associative memory, event-driven computation, asynchronous retrieval, neuromorphic memory, storage capacity, KLR Hopfield, margin maximization.Votes: 0GitHub stars: 3
- Event Driven Neuromorphic TransceiverEvent-driven impulse radio transceiver system for reliable wireless neuromorphic inference. Ultra-low power event-based communication optimized for spike-based neural network data transmission. Triggers: event-driven radio, neuromorphic transceiver, impulse radio, spike transmission, wireless SNN.Votes: 0GitHub stars: 3
- Event2vec Neuromorphic RepresentationEvent2Vec: Processing neuromorphic events directly via vector representations for efficient event camera data processing compatible with Transformer architectures. Activation triggers: event camera, neuromorphic vision, event2vec, DVS, asynchronous events, sparse events, event-based vision.Votes: 0GitHub stars: 3
- Evolutionary Le Chateliers Principle Timescale SeparationEvolutionary Le Chatelier's Principle methodology for understanding phenotypic plasticity and genetic assimilation through timescale separation in the Price equation, providing a physical mechanism for how rapid phenotypic responses precede slower genetic change.Votes: 0GitHub stars: 3
- Evolutionary Snn ClassifierEvolutionary feature selection for spiking neural network pattern classifiers using the biologically realistic JASTAP model. Combines evolutionary algorithms with SNN training for simultaneous architecture and feature optimization.Votes: 0GitHub stars: 3
- Evolvable Graph Diffusion Ot可进化图扩散最优传输脑连接组建模方法（EDT-PA）。结合结构-功能连接对齐和高阶依赖建模，用于脑疾病分类。触发词：脑连接组、最优传输、optimal transport、结构-功能对齐、高阶依赖、brain connectome、EDT-PA。Votes: 0GitHub stars: 3
- Evolved Instruction Following Inductive BiasEvolutionary inductive bias enabling rapid instructed task learning (RITL) in humans - bridges cognitive science, neuroscience, and LLM instruction tuningVotes: 0GitHub stars: 3
- Evotrace Evolutionary Coding AnalysisEvoTrace and EvoReplay methodology for diagnosing what evolutionary coding agents actually evolve. LLM-as-judge edit annotation, replay-based search state reconstruction, and controlled intervention analysis for agentic evolutionary search beyond final benchmark scores. Activation: evolutionary coding agent, LLM code evolution, EvoTrace, agentic search analysis, code generation mechanism.Votes: 0GitHub stars: 3
- Exact Ensemble Controllability Neural Differential EquationsExact ensemble controllability for neural differential equations via neural interpolation - constructive solution for steering multiple initial states to corresponding target states with a single set of control parameters in neural dynamics systems.Votes: 0GitHub stars: 3
- Exact First Passage Time Response TheoryUse for MFPT response analysis in neural dynamics.Votes: 0GitHub stars: 3
- Exclusion Statistics Quantum Heat EnginesExclusion statistics as a thermodynamic resource in quantum heat engines — using particle statistics interpolation (fermion/boson/anyon) as a design parameter for quantum thermal machines. From arXiv:2606.19310.Votes: 0GitHub stars: 3
- Existing Skills Integration WorkflowWorkflow for integrating existing ai_collection skills into current research sessions when papers are rediscovered during automated arXiv searches. Handles syncing local skills, updating INDEX.md, and maintaining knowledge base consistency.Votes: 0GitHub stars: 3
- Experiment As Code LabsExperiment-as-Code (EaC) Labs — a declarative stack for AI-driven scientific discovery. Encodes experiments as declarative configurations compiled to device-level APIs, with three-layer architecture: specification (standardization/reproducibility), execution (safety/reliability), and orchestration (scalability/efficiency). Inspired by Infrastructure-as-Code (IaC) for cloud computing, adapted for physical lab automation. Use when designing autonomous lab systems, AI-scientist physical executio...Votes: 0GitHub stars: 3