Business & Operations

Operations, strategy, finance, sales, support, management, and planning

skills in category: 29,837
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Showing 10,465–10,488 of 29,837 skills

Cocot Eeg Contrastive FoundationAContrastive pretraining methodology for EEG foundation models using multiscale convolutional Transformer architecture. Demonstrates contrastive learning as a superior alternative to masked reconstruction pretraining for EEG, which has high noise and narrow-band information. Achieves SOTA on heterogeneous electrode configurations. Activation: EEG contrastive learning, CoCoT, EEG foundation model, masked reconstruction, multiscale temporal convolution, self-supervised EEG, electrode heterogeneo...businessgoperformanceVotes: 0GitHub stars: 3
Cnn Snn Imagined Speech DecodingAEEG-based imagined speech decoding using hybrid CNN-SNN architecture. First integration of spiking neural networks for imagined speech BCI, achieving 80.13% accuracy on BCI Competition III benchmark. Covers CNN feature extraction, SNN temporal classification, and neuromorphic BCI pipeline design.businessgotestingVotes: 0GitHub stars: 3
Classical Disjunction Effect ModelAClassical probability model that reproduces the disjunction effect in human decision making without violating the law of total probability. Use when analyzing the disjunction effect, Prisoner's Dilemma decision paradox, quantum-like cognition models, classical vs quantum decision models, or ambiguity representation in choice behavior.businessexpressVotes: 0GitHub stars: 3
Causal Learning Neural AssembliesADIRECT mechanism for causal learning with neural assemblies - local plasticity-based directional learning without backpropagation. Enables neural assembly networks to internalize causal directionality through projection, local plasticity control, and sparse winner selection.businesspythongoVotes: 0GitHub stars: 3
Categorical Braiding SubfactorABraiding structures on categorical multi-interval Jones-Wassermann subfactor planar algebras from unitary modular fusion categories. Constructs braidings inducing projective unitary representations of balanced superelliptic mapping class groups, encoding higher-genus topological data. New proof of subfactor self-duality. Activation: braiding structures, Jones-Wassermann subfactor, planar algebra, modular fusion category, mapping class group, higher-genus topology, categorical quantumbusinessgoVotes: 0GitHub stars: 3
Brain Segmentation Active LearningAEntropy-based active learning methodology for fair and efficient brain image segmentation. Use when: (1) performing brain MRI/CT segmentation with limited labeled data, (2) needing fair segmentation across demographic groups, (3) selecting most informative samples for annotation, (4) optimizing annotation budget for medical imaging, (5) addressing bias in brain segmentation models.businessgoperformanceVotes: 0GitHub stars: 3
Brain Of Omnifunctional Foundation ModelABrain-OF: First omnifunctional brain foundation model jointly pretrained on fMRI, EEG and MEG. Uses Any-Resolution Neural Signal Sampler, DINT attention with Sparse MoE, and Masked Temporal-Frequency Modeling for dual-domain pretraining. Pretrained on ~40 datasets. Source: arXiv:2602.23410 (Guo et al., Feb 2026).businesspythonperformanceVotes: 0GitHub stars: 3
Brain Dit Fmri Foundation Model V5ABrain-DiT v5 universal multi-state fMRI foundation model with pre-training and fine-tuning for zero-shot and few-shot brain decoding across multiple states. Supports cross-task, cross-subject, and cross-dataset fMRI analysis using diffusion transformer architecture. Use when: fMRI foundation models, brain decoding, diffusion transformers for neuroimaging, cross-subject fMRI analysis, zero-shot brain state prediction, multi-task fMRI modeling, neural state decoding, fMRI pre-training. Activati...businesspythonVotes: 0GitHub stars: 3
Brain Connectivity AnalysisABrain network connectivity analysis using knowledge graph tools. Analyze brain connectivity patterns, neural networks, and graph-based brain models. Use when working with brain graphs, connectivity matrices, neural network analysis, or integrating neuroscience papers into knowledge graphs. Supports PageRank for important nodes, Louvain community detection, and similarity search for related research.businesspythongoVotes: 0GitHub stars: 3
Bispikclm Binary Spiking LlmABiSpikCLM methodology — the first fully binary spiking MatMul-free causal language model. Integrates Softmax-Free Spiking Attention (SFSA) and Spike-Aware Alignment Distillation (SpAD) to train energy-efficient spiking LLMs. Use when building spiking language models, energy-efficient NLP, binary spiking networks, spiking attention mechanisms, or knowledge distillation for SNNs. Trigger words: spiking language model, binary spiking, softmax-free attention, spike-aware distillation, BiSpikCLM, ...businessgitperformanceVotes: 0GitHub stars: 3
Bio Quantum Pso OptimizationAHybrid optimization combining quantum-behaved particle swarm optimization with bio-inspired swarm intelligence mechanisms. Integrates quantum-probabilistic position updates with ant colony and bee foraging behavior for multimodal and biologically structured search landscapes. Use when solving complex optimization problems requiring global search with local refinement, multimodal optimization, or hybrid quantum-bio approaches.businessgoperformanceVotes: 0GitHub stars: 3
Bayesian Neural Portfolio ManagementABayesian neural network methodology for robust portfolio management in dynamic financial markets. Uses Bayesian inference to quantify uncertainty in portfolio optimization, adapt to changing market conditions, and provide probabilistic risk assessments. Use when building portfolio management systems with uncertainty quantification, dynamic market adaptation, or probabilistic risk modeling.businessgoperformanceVotes: 0GitHub stars: 3
Asynchronous Quantum Distributed ComputingAAsynchronous quantum distributed computing - implementing global quantum operations in distributed systems. Combines classical distributed algorithms (Chandy-Lamport) with quantum computing principles. Activation: quantum distributed, quantum snapshot, quantum causality, QGO algorithm.businesspythongoVotes: 0GitHub stars: 3
Arxiv 2608 05716 Blockpython A Process Aware Agent Supported PlatfoABlockPython: A Process-Aware Agent-Supported Platform for the Transition from Block-Based to Python Programming (arXiv: 2608.05716)businesspythonVotes: 0GitHub stars: 3
Arxiv 2607 21292 An Llm Driven Workflow For Automated Process ContrAAn LLM-Driven Workflow for Automated Process Control Strategy Generation and Tuning from Dynamic Pro (arXiv: 2607.21292)businessVotes: 0GitHub stars: 3
Anthropic Economic Index Report CadencesAAnthropic Economic Index report: CadencesbusinesspythongoVotes: 0GitHub stars: 3
Anai Autonomous InfrastructureAAI-Native Autonomous Infrastructure (ANAI) formal framework methodology for evaluating AI as systemic infrastructural transition. Core constructs: Autonomy Index (AIx), Infrastructure Coupling Coefficient (ICC), Technological Transition Potential (TTP). Activation: AI-native infrastructure, autonomous infrastructure, GPT analysis, technology transition, infrastructure coupling.businesspythongoVotes: 0GitHub stars: 3
Algebraic Quantum Code ConcatenationACode concatenation methodology for quantum error correction using algebraic outer codes over high-rate quantum LDPC inner codes. Treats inner code blocks as logical Galois qudits, enabling concatenation with quantum Reed-Solomon outer codes and list decoders. Achieves teraquop regime with lower space overhead. Activation: quantum error correction, code concatenation, quantum LDPC, Galois qudit, Reed-Solomon quantum code, list decoding, fault tolerance, teraquop.businessgoperformanceVotes: 0GitHub stars: 3
Algebraic Mind VacoaAHow to Build Marcus's Algebraic Mind: Algebro-Deterministic Substrate over Galois Fields (arXiv:2605.21379). Maps Gary Marcus's three pillars of cognitive architecture (operations over variables, recursively structured representations, individual/kind distinction) onto the PyVaCoAl/VaCoAl hyperdimensional computing architecture. Uses XOR-and-shift over GF(2) as a single algebraic primitive. Activation: vacoal, hyperdimensional computing, algebraic mind, Gary Marcus, cognitive architecture, re...businesspythongoVotes: 0GitHub stars: 3
Project Vend Phase TwoAAnthropic's autonomous AI shopkeeper experiment investigating real-world business task performance, multi-agent coordination (CEO + worker), and emergent behaviors in commercial settings.businesspythonrustVotes: 0GitHub stars: 3
Probabilistic Memory Trustworthy EdgeAProbabilistic memory (p-MEM) — unified memory primitive for trustworthy edge intelligence that stores distribution parameters and samples at native memory bandwidthbusinessrustapiVotes: 0GitHub stars: 3
Interpretable Neuralsymbolic Concept ReasoningA**arXiv ID:** 2304.14068 **Authors:** Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Lio', Frederic Precioso, Mateja Jamnik, Giuseppe Marra **Published:** 2023-04-27T09:58:15Z **Abstract:** Deep learning methods are highly accurate, yet their opaque decision process prevents them from earning full human trust. Concept-based models aim to address this issue by learning tasks based on a set of human-understandabl...businessrustVotes: 0GitHub stars: 3
Early Stopping By Correlating Online Indicators In Neural NetworksA**arXiv ID:** 2402.02513 **Authors:** Manuel Vilares Ferro, Yerai Doval Mosquera, Francisco J. Ribadas Pena, Victor M. Darriba Bilbao **Published:** 2024-02-04T14:57:20Z **Abstract:** In order to minimize the generalization error in neural networks, a novel technique to identify overfitting phenomena when training the learner is formally introduced. This enables support of a reliable and trustworthy early stopping condition, thus improving the predictive power of that type of modeling. Our pr...businessrustVotes: 0GitHub stars: 3
Amm Fairness ImpossibilityAArrovian impossibility theorem for Automated Market Maker (AMM) design. Proves no aggregation rule for weighted-product AMMs can be simultaneously fair and strategy-proof when n>2 liquidity providers. Key result: fairness forces mean-type aggregation (weighted Aitchison centroid) while strategy-proofness forces median-type; only single-provider dictatorship satisfies both. Obstruction vanishes at n=2. Applies to DeFi protocol design, mechanism design, and prediction markets. (arXiv: 2606.04959)businessgoapiVotes: 0GitHub stars: 3