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SkillsMP has collected 4,114 skills from hiyenwong/ai_collection. Open a skill to review its source and details.
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Mean-field theory linking microscale synaptic motifs to macroscale neural population dynamics. Phenomenological framework integrating connectivity, synaptic transmission, plasticity, and heterogeneity.
Mean-field theory linking microscale synaptic motifs to macroscopic heterogeneous population dynamics. Bridges synaptic-resolution connectomics with nonlinear neural dynamics via low-rank mean-field equations. Applicable to RNN analysis, neural population…
Syndrome resampling methodology for enhancing quantum error correction thresholds. Increases QEC thresholds of any decoder and suppresses logical errors without additional hardware by biasing syndrome averages towards most likely syndromes. Establishes…
Synthetic Biological Intelligence (SBI) methodology — engineered systems where living Biological Neural Networks (BNNs) are interfaced with hardware/software for task-oriented information processing. Combines organoid technology, MEAs, neuromorphic computing,…
Texture Interpolation for Visual Perception
Algebraic quantum model where brain functions emerge as thermal equilibrium states of the connectome. Uses KMS formalism and C. elegans connectome. arXiv:2408.14221
Deep topographic multimodal model (Topo-Omni) for discovering functionally selective brain regions with contiguous spatial organization across visual, auditory, and language/cognitive modalities.
Topo-Omni deep topographic multimodal model for discovering functionally selective brain regions across visual, auditory, and language processing streams. Activation: topographic model, multimodal brain model, cortical organization, brain regions discovery.
Information-theoretic framework coupling Hodge decomposition with lead-lag mutual information for directed brain network analysis - separates feed-forward drive, feedback loops, and cyclic flow around topological holes.
Topological sensitivity analysis of connectome-constrained neural networks. Studies how network topology affects dynamical behavior and sensitivity to perturbations in brain connectome models. Applicable to robust brain dynamics analysis and lesion studies.
Topology-Dependent Emergence of Polychronous Neuronal Groups using Recurrence-Plot characterization. Small-world topology as structural optimum for polychronization with label-free PNG identification via sparse-dot-product Recurrence Plot framework.
TRACED: Activation Cascade Root-Cause Analysis
Trajectory-based computation of controlled invariant sets for linear discrete-time systems and MPC. Use when computing maximal controlled invariant sets, designing MPC without terminal sets, or needing recursive feasibility guarantees. Keywords: controlled…
Transformer 表征轨迹几何分析方法论 - 将计算神经科学的几何工具应用于 Transformer 可解释性研究，无需探测即可分析表征动力学
Source text: Chinese
Transcranial photobiomodulation (tPBM) therapy for insomnia using EEG biomarkers. Prefrontal cortex near-infrared light stimulation targeting prefrontal hypoactivity and hyperarousal model. Pilot study with college students using EEG spectral analysis and…
Treatment-Conditioned Diffusion framework for forecasting neurodegenerative disease progression via high-fidelity brain state prediction. Conditions generative process on DaTscan images and levodopa equivalent daily dose. Activation: neurodegenerative,…
统一冯诺依曼HPC与神经形态计算的EBRAINS工作流框架 - 透明跨平台执行SNN，trigger_words: neuromorphic computing. spiking neural network. SNN. HPC. EBRAINS. SpiNNaker. cross-platform. containerization. NESTML
Source text: Chinese
Decomposition methodology for identifying universal vs model-specific dimensions in vision model representations across 162 diverse models. Universal dimensions are more interpretable, driven by conceptual image properties, and better predict macaque IT…
大脑启发式记忆架构方法论 - 将用户记忆分离为内容层（海马体式 engram）和技能层（新皮层式共享 adapter），实现高效个人化 LLM
Source text: Chinese
Multi-level representational probing framework for digital twins of mouse V1. Systematically probes latent representations in neural activity-predicting models across three levels: (i) linear decodability from controlled visual probes, (ii) latent-unit tuning…
Beyond Neural Activity Prediction: Probing Latent Representations in Mouse V1 Digital Twins. Systematic multi-level probing framework for evaluating latent representations in sensory cortex digital twins, across linear decodability, latent-unit tuning, and…
Variational Autoencoder (VAE) framework for learning task-specific quantum embeddings of classical data. Compresses high-dimensional datasets (including ImageNet) into compact quantum representations (e.g., 13-qubit) while remaining reconstructable through a…
Valence bond embedding methodology for mapping deep quantum chemistry computations onto shallow quantum circuits, reducing NISQ resource requirements.
Variational Phasor Circuits (VPC) for phase-native Brain-Computer Interface classification using continuous S1 unit circle manifold with trainable phase shifts and unitary mixing
Variational framework for statistical inference on cyclic interactions in directed networks. Directed interactions as edge flows on simplicial complex evolved under energy-minimizing dynamics, yielding low-dimensional cycle space for recurrent organization.…
Verifiable Evol-Instruct framework for scaling multimodal mathematical reasoning. Type-aware evolution + HTV-Agent verifier with offline hypothesis-test falsification ensures reliable reward labels at scale.
ViSAE (Visual Sparse Autoencoder for Interpretability) - Neuroscience-motivated concept circuits framework for interpreting and steering Vision Transformers. Uses 64K images with 16K visually grounded concept vocabulary, achieving 20x efficiency improvement…
Multi-Stage Warm-Start (MSWS) deep learning framework for Unit Commitment optimization. Combines neural network warm-starting with MILP constraints to accelerate power grid scheduling. Use for unit commitment, power system optimization, energy scheduling, and…
Universal organizational regularity showing weight geometry governs functional memory in complex systems across biological, ecological, social, and technological domains. Activation: weight geometry, functional memory, complex systems, interaction strength,…
Exact formulas and bivariate master identity methodology for weighted partitions with interval restrictions. Use when: deriving generating functions for restricted partition functions, proving partition coefficient bounds via Rogers-Fine evaluation,…
Whisper-ECoG alignment methodology mapping speech foundation model representations to human cortical activity using interpretable time-resolved neural encoding
Winner-Take-All (WTA) bottlenecks enforce disentangled symbolic representations in multi-task learning. Shows WTA circuits (a core cortical motif) within deep networks extract categorical latent factors where single neurons encode single abstract features…
WorldKV methodology from arXiv:2605.22718 (May 2026). Training-free KV-cache management for autoregressive video diffusion world models: World Retrieval (evicted KV-chunk reuse) + World Compression (token pruning via key-key similarity). Use when: world model…
YANA: Bridging the Neuromorphic Simulation-to-Hardware Gap. Framework for seamless translation of SNN algorithms from simulation to neuromorphic hardware deployment. Activation: YANA, simulation-to-hardware, neuromorphic deployment, SNN hardware gap.
Anthropic research (Jun 8, 2026) — Methodology for measuring large language model impact on N-day exploit development and vulnerability exploitation timelines.
Prediction market pricing benchmark methodology — comparing prediction market prices (Polymarket) with option-implied risk-neutral probabilities from centralized exchanges (Binance/Deribit). Use when analyzing prediction market efficiency, cross-venue price…
LLM+RAG methodology for automated Qiskit code migration across versions. Uses taxonomy-based RAG to reduce hallucinations and improve code reliability in Quantum Software Engineering (QSE). Activation: qiskit migration, quantum code migration, QDK version…
Sparsely gated tiny linear experts (sgatlin) methodology — replacing transformer feedforward layers with networks of sparsely-gated linear neurons for improved compute efficiency and interpretability. Covers isoflop comparison, linear expert removal of…
Uncertainty-Aware LLM-Guided Policy Shaping for sparse-reward RL. Integrates calibrated LLM into RL training loop with uncertainty-modulated behavioral guidance.
Uncertainty-aware LLM-guided policy shaping for sparse-reward RL using A* oracle trajectories and entropy-based blending with MC dropout uncertainty estimation.