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- Network Attractors Delay PlasticityNetwork Attractors driven by Time-Delay Plasticity — framework for collective frequency selection and attractor formation via adaptive axonal delays (AADs), motivated by activity-dependent myelination in the brain. Uses delay-coupled phase oscillators on brain connectivity data. Activation: delay plasticity, adaptive axonal delay, network attractor, frequency selection, neural oscillation, myelination model, phase oscillator brain networkVotes: 0GitHub stars: 3
- Memory Uncertainty Relation Recurrent NetworksMemory Uncertainty Relation in random recurrent networks: inequality bounding short-term memory from below as an uncertainty relation between memory capacity and state-space fluctuations. Defines harmonic memory as an analytically tractable lower bound achieved by optimal readout weights.Votes: 0GitHub stars: 3
- Maximum Entropy Network Structure FunctionMaximum entropy principle for neural network connectivity that reveals how task constraints shape neural population structure without dependence on training procedure. Use when analyzing neural connectivity patterns, studying structure-function relationships, or designing normative models of neural computation.Votes: 0GitHub stars: 3
- Local Gradient Approximations RnnDynamics and Representation Structure of Local Approximations to Gradient-Based Learning in Linear Recurrent Neural Networks. Analytical framework comparing RFLO, tBPTT, and BPTT learning dynamics using dynamical systems theory. Key finding: RFLO solutions restricted to low-rank perturbations, with qualitatively distinct convergence behavior.Votes: 0GitHub stars: 3
- Llm Sysml AlignmentLLM-assisted semantic alignment methodology for SysML v2 model integration in collaborative MBSE. Use when working with cross-organizational system model integration, SysML v2 semantic alignment, or LLM-based MBSE workflows. Keywords: SysML, MBSE, LLM, semantic alignment, model integration, SysML v2.Votes: 0GitHub stars: 3
- Llm Icl Representational Geometry ReorganizationNeuroscience-inspired geometric account of in-context learning (ICL) in LLMs — how representational geometry reshapes to support online untangling and classification without parameter updates.Votes: 0GitHub stars: 3
- Llm Emotion ConceptsMethodology for identifying and analyzing functional emotion representations in LLM internals. Covers finding emotion-related neural activity patterns, testing their causal influence via activation steering, and understanding how abstract emotion concepts shape model behavior. Use when: (1) analyzing LLM emotional behavior, (2) studying representation causality, (3) investigating model decision-making driven by internal states, (4) safety research on models taking undesirable actions under em...Votes: 0GitHub stars: 3
- Lighthouse AttentionLong Context Pre-Training with Lighthouse Attention — NousResearch 提出的对称选择式分层注意力算法。面向超长上下文预训练，通过对称 Q/K/V 金字塔池化、无参数打分 top-K 选择、选择与注意力解耦、两阶段训练，实现 O(N·d) 复杂度。触发词：lighthouse attention, long context pretraining, hierarchical attention, symmetric pooling, sparse attention, FlashAttention wrapperVotes: 0GitHub stars: 3
- Learning Based Robust Control Free EnergyDistributionally robust free energy principle for reliable robotic control. Jointly learns environment dynamics and rewards while ensuring robustness to epistemic uncertainties. Validated on Franka Research 3 arm manipulation tasks.Votes: 0GitHub stars: 3
- Kinetic Energy Random Rnn ChaosKinetic energy in random recurrent neural networks - links chaotic dynamics and unstable fixed points through dynamical mean-field theory. Cubic scaling at critical point, shell-like chaotic manifold geometry. Activation: kinetic energy, random RNN, chaos, dynamical mean-field theory, chaotic dynamics, fixed points.Votes: 0GitHub stars: 3
- Ip3r Bayesian Missed Event ModelingBayesian modeling methodology for ion channel gating with missed event correction. Integrates temporal resolution limitations of patch clamp recordings into hierarchical Markov chain likelihood functions, enabling unbiased kinetic parameter inference and model selection for IP3R calcium channels. Reveals multimodal gating behavior with Park/Drive mode switching regulated by Ca2+ concentration. Use when: modeling ion channel kinetics, analyzing single-channel patch clamp data, correcting for m...Votes: 0GitHub stars: 3
- Integrative Neurocybernetic ModelingIntegrative neurocybernetic modeling framework for large-scale neuroscience. Treats brain as controller pursuing latent objectives in closed-loop coupling with body and environment. Keywords: neurocybernetics, closed-loop modeling, large-scale neuroscience, brain-body-environment coupling, nonlinear state-space modelsVotes: 0GitHub stars: 3
- Hopfield Continual Learning DiffusionModern Hopfield Networks for continual learning in diffusion models via energy-based intrinsic forgetting and replay selectionVotes: 0GitHub stars: 3
- Holos Agentic Web Multi AgentWeb-scale LLM-based multi-agent system architecture for the Agentic Web. Focuses on five-layer coordination architecture, heterogeneous agent interaction, and open-world scaling challenges. Use when: (1) Designing large-scale multi-agent systems, (2) Implementing web-scale agent coordination, (3) Building agentic web architectures, (4) Studying LLM-based multi-agent systems, (5) Understanding agent ecosystem evolution toward AGI.Votes: 0GitHub stars: 3
- Gnn Transformer Fusion图神经网络与 Transformer 融合的多模态数据融合方法论。 整合非欧几里得脑影像数据与欧几里得表格数据，支持时间感知的纵向预测。 触发词：多模态融合、脑网络、GNN、Transformer、时序预测、纵向分析、 multimodal fusion, brain connectivity, GNN-TF, temporal fusion。Votes: 0GitHub stars: 3
- Gffmerge Model Merging GnnsGFFMERGE methodology for efficient closed-form model merging in Graph Neural Networks. Exploits linear structure of message-passing layers to enable near-quantum accuracy atomistic simulations without retraining foundation models. Applicable to drug discovery, materials science, and general GNN transfer. Activation: GNN model merging, graph neural network transfer, neural force field merging, molecular simulation, atomistic GNN, quantum accuracy GNN, convex embedding alignmentVotes: 0GitHub stars: 3
- Game Energetic Ei Networks**Problem**: Classical energy-based models require symmetric weight matrices, excluding biologically realistic E-I networks with asymmetric connectivity.Votes: 0GitHub stars: 3
- Free Energy Principle Moe RoutingFree Energy Principle-based MoE routing using LIF membrane dynamics. Solves domain transition failures in sparse MoE with three mechanisms: temporal memory (beta), precision-weighted gating (Pi), and anticipatory routing. 124x improvement at transitions. Activation: free energy principle, MoE routing, domain transition, predictive routing, LIF gating, Friston, mixture of experts.Votes: 0GitHub stars: 3
- Free Energy Moe RoutingFree Energy Principle-based Mixture-of-Experts routing methodology. Uses LIF membrane potentials (beta) for temporal memory, precision-weighted gating (Pi) for reliability assessment, and anticipatory routing to solve domain transition failures in sparse MoE. Trigger words: free energy MoE, MoE routing failure, domain transition, LIF gating, precision-weighted routing, anticipatory routing, mixture of experts failure, sparse MoE, expert affinity.Votes: 0GitHub stars: 3
- Fcn Llm Graph TuningFCN-LLM: Empowering LLMs for Brain Functional Connectivity Network Understanding via Graph-level Multi-task Instruction Tuning. Covers the multi-scale FCN encoder, semantic projection into LLM, 19-attribute multi-paradigm instruction tuning, two-stage learning strategy, and zero-shot generalization. Based on arXiv 2603.01135.Votes: 0GitHub stars: 3
- Ei Network Chaos Synchrony TheoryExtended Sompolinsky-Crisanti-Sommers (SCS) chaos theory for Excitatory-Inhibitory recurrent networks with target-specific inhibition. Derives mean-field theory for E/I networks, identifies three dynamical regimes (quiescence, asynchronous chaos, coherent oscillations), and shows coherent oscillations suppress chaos. Activation: chaos-synchrony, SCS theory, E/I balance, target-specific inhibition, dynamical mean-field theory, neural phase diagram, recurrent network dynamics, excitation-inhibi...Votes: 0GitHub stars: 3
- Economy Of Minds Multi Agent IntelligenceEconomy of Minds - Multi-agent intelligence emerging from economic interactions (auctions, payments, wealth accumulation). Decentralized self-orchestration without explicit communication protocols. Inspired by Hayek's economic theory. Activation: multi-agent economy, decentralized coordination, economic selection, agent auctions, wealth accumulation, Hayek theory, emergent intelligence, self-organization. Tags: multi-agent, economics, decentralized, self-organization, coordination, auctions, ...Votes: 0GitHub stars: 3
- Dynamic Gradient Gating RlvrDynamic Gradient Gating (DGG) methodology for sample-efficient RLVR - monitoring lm_head gradient norm to detect harmful policy shift and intercept gradients before corruptionVotes: 0GitHub stars: 3
- Dsm Llm ModularizationLLM-based Design Structure Matrix (DSM) modularization methodology. Use when partitioning complex systems into cohesive modules, optimizing system architecture, or applying LLMs to combinatorial engineering problems. Activation triggers: DSM, design structure matrix, system modularization, architecture decomposition, LLM combinatorial optimization, semantic alignment hypothesis, engineering design optimization.Votes: 0GitHub stars: 3