Business & Operations

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

skills in category: 29,837
pages available: 1,244

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 browser

Browse business & operations skills

Showing 10,321–10,344 of 29,837 skills

Lonic Algorithm Hardware CodesignALonic: INT4 algorithm-hardware co-design for SNNs.businessgogitVotes: 0GitHub stars: 3
Learning Successor Features With Distributed Hebbian Temporal MemoryA**arXiv ID:** 2310.13391 **Authors:** Evgenii Dzhivelikian, Petr Kuderov, Aleksandr I. Panov **Published:** 2023-10-20T10:03:14Z **Abstract:** This paper presents a novel approach to address the challenge of online sequence learning for decision making under uncertainty in non-stationary, partially observable environments. The proposed algorithm, Distributed Hebbian Temporal Memory (DHTM), is based on the factor graph formalism and a multi-component neuron model. DHTM aims to capture sequenti...businessgoVotes: 0GitHub stars: 3
Learning Plannable Representations With Causal InfoganA**arXiv ID:** 1807.09341 **Authors:** Thanard Kurutach, Aviv Tamar, Ge Yang, Stuart Russell, Pieter Abbeel **Published:** 2018-07-24T20:46:05Z **Abstract:** In recent years, deep generative models have been shown to 'imagine' convincing high-dimensional observations such as images, audio, and even video, learning directly from raw data. In this work, we ask how to imagine goal-directed visual plans -- a plausible sequence of observations that transition a dynamical system from its current con...businessgoVotes: 0GitHub stars: 3
Learning By Active Forgetting For Neural NetworksA**arXiv ID:** 2111.10831 **Authors:** Jian Peng, Xian Sun, Min Deng, Chao Tao, Bo Tang, Wenbo Li, Guohua Wu, QingZhu, Yu Liu, Tao Lin, Haifeng Li **Published:** 2021-11-21T14:55:03Z **Abstract:** Remembering and forgetting mechanisms are two sides of the same coin in a human learning-memory system. Inspired by human brain memory mechanisms, modern machine learning systems have been working to endow machine with lifelong learning capability through better remembering while pushing the forgett...businessgoVotes: 0GitHub stars: 3
How The Tensor Brain Uses Embeddings And Embodiment To Encode Senses And SymbolsA**arXiv ID:** 2409.12846 **Authors:** Volker Tresp, Hang Li **Published:** 2024-09-19T15:45:38Z **Abstract:** The Tensor Brain (TB) has been introduced as a computational model for perception and memory. This paper provides an overview of the TB model, incorporating recent developments and insights into its functionality. The TB is composed of two primary layers: the representation layer and the index layer. The representation layer serves as a model for the subsymbolic global workspace, a co...businessVotes: 0GitHub stars: 3
Geometric Laplace Transform SystemsAGeometric Algebra Laplace transforms for system analysis.businessjavascriptpythonVotes: 0GitHub stars: 3
Finite Reliability RepresentationsAFinite Reliability Representations (FRR) methodology for noise-calibrated belief-space covers in decision-making systems. Provides certified suboptimality bounds based on sensing, process, and actuation noise. Use when designing reliable decision systems, POMDP policies, or safety-critical control.businessperformanceVotes: 0GitHub stars: 3
Do You Remember Toward Memory Centric Multimodal AADerived from arXiv:2607.11919 - Do You Remember? Toward Memory-Centric Multimodal AIbusinessVotes: 0GitHub stars: 3
Controllability Multiplexing And Transfer Learning In Networks Using Evolutionary LearningA**arXiv ID:** 1811.05592 **Authors:** Rise Ooi, Chao-Han Huck Yang, Pin-Yu Chen, Vìctor Eguìluz, Narsis Kiani, Hector Zenil, David Gomez-Cabrero, Jesper Tegnèr **Published:** 2018-11-14T01:36:52Z **Abstract:** Networks are fundamental building blocks for representing data, and computations. Remarkable progress in learning in structurally defined (shallow or deep) networks has recently been achieved. Here we introduce evolutionary exploratory search and learning method of topologically flexibl...businessgonodeVotes: 0GitHub stars: 3
Compound Pulse Gadget SynthesisAHolistic pulse synthesis methodology for quantum algorithms that bypasses discrete gate-stitching to compile algorithms directly into continuous compound pulse gadgets. Use when optimizing quantum circuits for trapped-ion or superconducting hardware, reducing gate overhead, minimizing decoherence exposure, or compiling QSVT/Hamiltonian simulation algorithms. Activation: compound pulse gadgets, GRAPE pulse engineering, holistic pulse synthesis, continuous pulse compilation, QSVT block-encoding...businessgoVotes: 0GitHub stars: 3
Competitive Complementary ToolsAThis skill implements the methodology from arXiv:2607.18460 "Competitive and Complementary Tools". The framework models the co-evolution of human competence and AI tool reliance as a bistable dynamical system, analyzing critical thresholds for competence collapse and agency transfer between humans and AI systems.businesspythonrustVotes: 0GitHub stars: 3
Bitwise Neural NetworksA**arXiv ID:** 1601.06071 **Authors:** Minje Kim, Paris Smaragdis **Published:** 2016-01-22T16:59:01Z **Abstract:** Based on the assumption that there exists a neural network that efficiently represents a set of Boolean functions between all binary inputs and outputs, we propose a process for developing and deploying neural networks whose weight parameters, bias terms, input, and intermediate hidden layer output signals, are all binary-valued, and require only basic bit logic for the feedforwa...businessperformanceVotes: 0GitHub stars: 3
Assemblies Of Neurons Learn To Classify Wellseparated DistributionsA**arXiv ID:** 2110.03171 **Authors:** Max Dabagia, Christos H. Papadimitriou, Santosh S. Vempala **Published:** 2021-10-07T03:53:39Z **Abstract:** An assembly is a large population of neurons whose synchronous firing is hypothesized to represent a memory, concept, word, and other cognitive categories. Assemblies are believed to provide a bridge between high-level cognitive phenomena and low-level neural activity. Recently, a computational system called the Assembly Calculus (AC), with a reper...businessgogitVotes: 0GitHub stars: 3
Arxiv SearchDarXiv paper search skill - search academic papers by keywords, authors, categories. Supports time filtering, category filtering, and paper detail retrieval. Activation: arxiv search, paper search, 论文搜索, search papers, arxiv 论文.businesspythonrustVotes: 0GitHub stars: 3
Arxiv 2608 30424v1 Towards Cognitive Process Aware Proactive WritingA**arXiv ID:** 2608.30424v1 **Authors:** Masahiro Yoshida, Atsuya Kobayashi, Kei Tateno, Xiang 'Anthony' Chen **URL:** http://arxiv.org/abs/2608.30424v1 **Utility Score:** 1.00businessVotes: 0GitHub stars: 3
Nuclear Lattice VqeAVariational Quantum Eigensolver (VQE) framework for nuclear lattice effective field theory. Computes ground state energies of light nuclei (2H, 3H, 4He) using Gray code encoding with symmetry reduction for compact qubit representation. Keywords: nuclear physics, VQE, variational quantum eigensolver, nuclear lattice EFT, Gray code encoding, Jordan-Wigner, light nuclei, deuterium, tritium, helium-4.businessgoreactVotes: 0GitHub stars: 3
Non Unitary Qml Fisher EfficiencyANon-unitary quantum machine learning via Linear Combination of Unitaries (LCU) framework, with Fisher efficiency transitions and threshold-dependent parameter scaling in medical imaging tasks. Use when: implementing non-unitary quantum layers, benchmarking quantum vs classical performance across domains, analyzing Fisher information efficiency in QML, or designing quantum circuits for medical image classification.businesspythongoVotes: 0GitHub stars: 3
Noise Directed Adaptive RemappingANoise-directed adaptive remapping methodology for integer optimization — encoding qubit-based problems into qudit representations with noise-aware adaptation. Use when optimizing quantum integer optimization on NISQ hardware, converting qubit encodings to qudit representations, mitigating hardware noise through adaptive remapping, or solving scheduling/resource allocation problems with quantum qudit systems.businessexpressVotes: 0GitHub stars: 3
Ssm Contraction ControlAController design for Structured State-space Models (SSMs) using contraction theory with indirect data-driven output feedback. Use when: (1) designing controllers for nonlinear systems identified via SSM surrogate models, (2) implementing contraction-based stabilization with Linear Matrix Inequality (LMI) conditions, (3) establishing separation principle for observer-controller design, (4) applying scalable control design to time-series and dynamical systems. First controllability/observabili...businessVotes: 0GitHub stars: 3
Llm Trading Agent AlignmentABehavioral alignment and representation dynamics analysis for LLM trading agents — pre-failure signatures, risk-feedback alignment, and manifold diagnostics for auditable financial decision-making. Use when building or analyzing LLM-based trading agents, studying agent behavioral alignment, detecting pre-failure signatures in financial LLM systems, or implementing structured risk feedback for trading agents.businessperformanceVotes: 0GitHub stars: 3
Fhe Privacy Preserving LlmAFully Homomorphic Encryption (FHE) patterns for privacy-preserving LLM inference. Covers lattice-based cryptography (LWE/RLWE), FHE scheme selection (BFV, BGV, CKKS), and techniques for running large models on encrypted data. Based on implementation of FHE on Llama 3 for secure computation. Use when: building privacy-preserving AI inference systems, implementing homomorphic encryption for ML models, or designing secure computation pipelines for sensitive data. arXiv: 2604.12168businessperformanceVotes: 0GitHub stars: 3
Do You Remember Toward Memorycentric Multimodal AiA**arXiv ID:** 2607.11919 **Authors:** Xuguang Yu, Weigang Zheng, Minyue Yu **Published:** 2026-07-07T19:07:27Z **Abstract:** Human memory is reconstructive, not a faithful recording. Current multimodal LLMs (MLLMs) lack this capability: they process images through a frozen visual encoder, produce a one-shot text output, and discard internal representations. We present DoYouRemember, a three-stage architecture introducing reconstructive memory into MLLMs: (1) a VQ-VAE compresses images into di...businessVotes: 0GitHub stars: 3
Bisco Llm Binary Spherical Coding Extreme CompressionACodebook-free binary spherical coding for extreme low-bit LLM weight compression. Maps weight chunks onto unit hypersphere and binarizes into sign streams. Residual BSQ stage for reconstruction error. Category-wise recovery distillation. Activation: binary spherical coding, LLM compression, low-bit quantization, lookup-free coding, model deployment.businessgoperformanceVotes: 0GitHub stars: 3
Neuroworld Latent Brain World ModelANeuroWorld - A Latent Brain World Model for Stimulus-Conditioned Human Brain Dynamics. Framework for causal forecasting of human brain activity using stimulus-conditioned evolution in learned latent brain-state space, separating endogenous states from exogenous multimodal stimuli. Use when modeling naturalistic brain functional dynamics prediction, brain world models, or fMRI-based neural state forecasting.businessapiperformanceVotes: 0GitHub stars: 3