All categories
Research
Research, evidence gathering, literature, reports, investigation, and synthesis
- 21,402
- 892
Security grades appear on each card once the skill has been scanned. Newly imported skills may briefly show without a grade until the backfill job runs.
Open in full browserBrowse research skills
Showing 11,737–11,760 of 21,402 skills
- Eccentricity Confound Eeg Visual AttentionEccentricity confound analysis for EEG-based visual attention decoding during natural video viewing. Methodological framework for separating true neural attention from stimulus and eye movement artifacts. Keywords: visual attention, EEG, eye movements, eccentricity, natural video, artifact removal.Votes: 0GitHub stars: 3
- Eccentricity Confound Eeg Visual Attention DecodingEEG-based visual attention decoding methodology addressing the eccentricity confound. Uses spatial attention tasks with controlled stimulus eccentricity and phase-scrambling controls to demonstrate that decodable EEG signals reflect genuine attention modulation, not visual processing confounds. Use when building EEG-based BCI attention decoders, visual attention research, or addressing confounds in neural decoding.Votes: 0GitHub stars: 3
- Earable Eeg Auditory PlatformIn-ear EEG monitoring platform methodology for simultaneous EEG sensing and auditory stimulation. Covers personalized IEEM device design, closed-loop neuromodulation, and in-ear electrode validation.Votes: 0GitHub stars: 3
- Dysco Latent Dynamics ExtractionDYSCO (Dynamics via Contrastive Learning) - 多视角对比学习从噪声观测中提取潜在动力学系统。通过独立噪声视角分离信号与噪声，恢复潜在轨迹和支配动力学方程。Votes: 0GitHub stars: 3
- Dynamical Isometry PlasticityContinual learning framework preserving plasticity via dynamical isometry - Neural Tangent Kernel analysis showing layer-wise Jacobian singular values near 1 prevents plasticity loss, with isometry-promoting regularization and dormant ReLU reactivation mechanisms.Votes: 0GitHub stars: 3
- Dynamic Path Brain ConnectivityModel dynamic path trajectories in brain functional connectivity to capture temporal evolution of connections between functional communities. Based on arXiv 2510.24025 NeuroPathNet.Votes: 0GitHub stars: 3
- Dynamic Neural Manifolds ControlDynamic neural manifolds methodology for flexible closed-loop control on neuromorphic hardware. From arXiv:2607.07373 (von Seeler et al., Jul 2026).Votes: 0GitHub stars: 3
- Dual Memory Pathway SnnDual Memory Pathway (DMP) neuromorphic network co-design methodology. Inspired by cortical fast-slow organization, combines explicit slow memory with fast spiking activity for long-timescale context. Applies to: neuromorphic computing, event-driven sensing, energy-efficient SNN deployment. Activation: dual memory pathway, neuromorphic co-design, fast-slow SNN, near-memory compute, cortical memory.Votes: 0GitHub stars: 3
- Dual Envelope Mpc Vehicle DriftDual-envelope constrained nonlinear MPC for autonomous vehicle drifting control. Methods for constructing stability envelopes in phase plane, model predictive control with envelope constraints, and handling bounded steering/yaw-moment control for distributed drive EVs. Triggers: vehicle drifting control, MPC envelope constraint, autonomous drifting, distributed drive EV, yaw moment control, saddle point stability, phase plane envelope.Votes: 0GitHub stars: 3
- Dual Axis Zebrafish Circuits斑马鱼被盖微电路双轴归因方法论。基于斑马鱼视网膜被盖微电路的双轴功能归因（能量高效信息处理和鲁棒稳定）方法，将生物学电路组织转化为类脑神经网络架构设计。适用于脉冲神经网络、类脑架构设计、电路归因。触发词：dual-axis, 双轴归因, zebrafish tectal, microcircuit attribution, energy efficiency, robustness, ns_TIN, superficial_TINVotes: 0GitHub stars: 3
- Drl Quantum Optimal ControlDeep reinforcement learning for quantum optimal control. Combines DRL with quantum gate synthesis to achieve high-fidelity, high-speed quantum operations without prior heuristic ansatz. Use when: (1) Designing quantum optimal control protocols, (2) Applying DRL to quantum gate synthesis, (3) Implementing incremental-update learning policies, (4) Optimizing Rydberg gate operations in neutral-atom quantum computers, (5) Multi-parameter pulse modulation for quantum control. Trigger: DRL quantum ...Votes: 0GitHub stars: 3
- Driada Cross Scale Neural AnalysisDRIADA: Open-source Python toolkit for cross-scale analysis of single-neuron selectivity and population dynamics. Unifies neural signals and behavior in shared data model for selectivity testing, dimensionality reduction, and network analysis. Activation: DRIADA toolkit, cross-scale neural analysis, single-neuron selectivity, population dynamics, hippocampal calcium imaging, neural coding toolkit, information-theoretic selectivity.Votes: 0GitHub stars: 3
- Dreaming World Action Models梦境推理与世界行动模型：将梦境的认知重组机制应用于多模态推理，实现适应性推理策略切换。核心：Dreaming-when-Necessary机制、多模态推理适应性、长程任务规划。触发词：梦境推理、世界模型、行动规划、dreaming、多模态推理、adaptive reasoning、长程任务。Votes: 0GitHub stars: 3
- Doob Barrier Noise ConsolidationDoob-barrier-conditioned diffusion methodology that turns analog device noise into a continual-learning resource for neuromorphic hardware. Uses Doob h-transform to condition synaptic weight dynamics on never crossing memory-critical barriers, creating a noise-amplified restoring force. Based on arXiv:2607.06924v1 (Howe, 2026).Votes: 0GitHub stars: 3
- Dmd High Frequency Eeg Brain Disorder DetectionDetecting high-frequency brain disorder signals using Dynamic Mode Decomposition (DMD) from EEG data. Extracts consistent dynamical changes in high-frequency bands to identify neurological patterns distinguishing clinical groups like alcohol-dependent patients from controls.Votes: 0GitHub stars: 3
- Distributed Quantum Control Systems系统工程学 + 量子计算融合模式。涵盖分布式量子计算架构、量子控制理论（H∞控制、反馈控制）、量子系统工程方法论。Activation: 分布式量子控制, quantum control systems, distributed quantum computing engineering, quantum systems engineering.Votes: 0GitHub stars: 3
- Distributed Quantum Compiler SchedulingCompiler techniques for scheduling and optimizing distributed quantum computers (DQCs). Covers teleportation-aware scheduling, utility-driven lookahead scheduling, EPR-capacity-aware early scheduling, frequency allocation and transpilation co-design, and code surgery synthesis for stabilizer codes. Use when: designing DQC compilers, optimizing quantum circuit scheduling across multi-chip systems, minimizing teleportation overhead, implementing lookahead-aware quantum compilation, scheduling c...Votes: 0GitHub stars: 3
- Dissipative Quantum ChaosDissipative quantum chaos methodology — extending Hamiltonian quantum chaos to open quantum dynamics via Lindbladian spectral analysis. Use when analyzing chaoticity of open quantum systems, distinguishing integrable from chaotic dynamics, or studying driven-dissipative quantum systems.Votes: 0GitHub stars: 3
- Discrete Signaling Chaotic Regularization RnnDiscrete signaling mediates chaotic regularization in recurrent neural networks - theoretical framework linking microscopic chaos to macroscopic geometry of neural representations. Activation: chaotic regularization, discrete signaling, RNN chaos, neural representation manifold, power-law spectrum, cortical chaos.Votes: 0GitHub stars: 3
- Discrete Heat Kernels SimplicialDiscrete Heat Kernels on Simplicial Complexes and Its Application to Functional Brain Networks. Unified framework for heat kernel smoothing on simplicial complexes extending classical signal processing methods to higher-order network structures.Votes: 0GitHub stars: 3
- Discovery By Dreaming Cross Domain RecombinationA skill for implementing cross-domain recombination inspired by dreaming, based on the paper \"Discovery by Dreaming: Cross-Domain Recombination in Artificial Memory\" (arXiv:2607.16256). This skill outlines how to implement a LoRA fine-tuning pipeline (DREAMS) and a symbolic engine (SAPIENCE) to recombine knowledge across domains, enhancing AI discovery and insight generation.Votes: 0GitHub stars: 3
- Discovering Cryptographic Weaknesses ClaudeDiscovering cryptographic weaknesses using Claude AI.Votes: 0GitHub stars: 3
- Directional Coordination Hierarchy BrainDirectional coordination hierarchy in large-scale brain dynamics — identifies three recurrent resting-state coordination regimes (feedback-dominated, feedforward-dominated, integrative), shows this framework is disrupted in schizophrenia, and links directional functional dynamics to symptom severity and cognition.Votes: 0GitHub stars: 3
- Direct Neural Assemblies Causal LearningDIRECT (DIRectional Edge Coupling/Training) methodology for causal learning with neural assemblies using local plasticity. Enables neural assemblies to internalize causal directionality without backpropagation. Activation triggers: neural assemblies, causal learning, directional learning, local plasticity, DIRECT mechanism, synaptic asymmetry, explainable causality.Votes: 0GitHub stars: 3