github.com/Vectorized/solady
Vectorized/solady
Optimized Solidity snippets. (⭐ 3280)
arxiv.org/abs/1705.07437v1
Powerful sets: a generalisation of binary matroids
A set $S\subseteq\{0,1\}^E$ of binary vectors, with positions indexed by $E$, is said to be a \textit{powerful code} if, for all $X\subseteq E$, the number of vectors in $S$ that are zero in the positions indexed by $X$ is a power of 2. By treating b...
arxiv.org/abs/2505.17810v1
VIBE: Vector Index Benchmark for Embeddings
Approximate nearest neighbor (ANN) search is a performance-critical component of many machine learning pipelines. Rigorous benchmarking is essential for evaluating the performance of vector indexes for ANN search. However, the datasets of the existin...
arxiv.org/abs/nlin/0406006v1
Time-dependent mode structure for Lyapunov vectors as a collective movement in q…
Time dependent mode structure for the Lyapunov vectors associated with the stepwise structure of the Lyapunov spectra and its relation to the momentum auto-correlation function are discussed in quasi-one-dimensional many-hard-disk systems. We demon...
arxiv.org/abs/2508.16354v2
Negatively curved Kähler metrics on total spaces of a class of vector bundles
In this paper we show an abundance of complete Kähler metrics with negative holomorphic bisectional curvature on total spaces of certain vector bundles. Assume that such total spaces are endowed with a wider class of nonpositively curved Kähler met...
arxiv.org/abs/2411.03965v1
Bayesian algorithmic perfumery: A Hierarchical Relevance Vector Machine for the…
This study explores a Bayesian algorithmic approach to personalized fragrance recommendation by integrating hierarchical Relevance Vector Machines (RVM) and Jungian personality archetypes. The paper proposes a structured model that links individual s...
arxiv.org/abs/2401.11246v1
Prompt-RAG: Pioneering Vector Embedding-Free Retrieval-Augmented Generation in N…
We propose a natural language prompt-based retrieval augmented generation (Prompt-RAG), a novel approach to enhance the performance of generative large language models (LLMs) in niche domains. Conventional RAG methods mostly require vector embeddings...
arxiv.org/abs/2002.04726v2
Online Learning with Imperfect Hints
We consider a variant of the classical online linear optimization problem in which at every step, the online player receives a "hint" vector before choosing the action for that round. Rather surprisingly, it was shown that if the hint vector is guara...
arxiv.org/abs/2509.07352v2
Directed searches for gravitational waves from ultralight vector boson clouds ar…
We present the first directed searches for long-transient and continuous gravitational waves from ultralight vector boson clouds around known black holes (BHs). We use LIGO data from the first part of the fourth LIGO-Virgo-KAGRA observing run. The se...
arxiv.org/abs/2411.01944v2
KPCA for Thrust Vectoring Systems Exhibiting Singular Points
This paper considers a class of thrust vectoring systems, which are nonlinear, overactuated, and time-invariant. We assume that the system is composed of two subsystems and there exist singular points around which the linearized system is uncontrolla...
arxiv.org/abs/2307.01153v2
Integral cohomology rings of weighted Grassmann orbifolds and rigidity propertie…
In this paper, we introduce `Plücker weight vector' and establish the definition of a weighted Grassmann orbifold $\mbox{Gr}_{\mathbf{b}}(k,n)$, corresponding to a Plücker weight vector `$\mathbf{b}$'. We achieve an explicit classification of weigh...
github.com/AndersonBY/vector-vein
AndersonBY/vector-vein
No-code AI workflow. Drag and drop workflow nodes and use your workflow with your AI agents. (⭐ 942)
arxiv.org/abs/hep-ph/9411291v1
The Bess Model at Future Colliders
The BESS model consists of an effective lagrangian parametrization with dynamical symmetry breaking, describing scalar, vector and axial-vector bound states in a rather general framework. After a brief description of the model and its generalizatio...
arxiv.org/abs/2504.08137v1
Empowering Vector Architectures for ML: The CAMP Architecture for Matrix Multipl…
This study presents the Cartesian Accumulative Matrix Pipeline (CAMP) architecture, a novel approach designed to enhance matrix multiplication in Vector Architectures (VAs) and Single Instruction Multiple Data (SIMD) units. CAMP improves the processi...
arxiv.org/abs/2510.25503v1
A Vector-Based Algorithm for Generating Complete Balanced Reaction Sets with Arb…
We present a vector-based method to balance chemical reactions. The algorithm builds candidates in a deterministic way, removes duplicates, and always prints coefficients in the lowest whole-number form. For redox cases, electrons and protons/hydroxi...
arxiv.org/abs/2510.25453v1
Vector-Based Approach to the Stoichiometric Analysis of Multicomponent Chemical…
The study demonstrates the capabilities of a vector-based approach for calculating stoichiometric coefficients in chemical equations, using black powder as an illustrative example. A method is proposed for selecting and constraining intermediate inte...
github.com/tensorchord/pgvecto.rs
tensorchord/pgvecto.rs
Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. (⭐ 2157)
arxiv.org/abs/1303.1152v2
An Equivalence between the Lasso and Support Vector Machines
We investigate the relation of two fundamental tools in machine learning and signal processing, that is the support vector machine (SVM) for classification, and the Lasso technique used in regression. We show that the resulting optimization problems...
arxiv.org/abs/2502.19659v1
Time-Varying Identification of Structural Vector Autoregressions
We propose a novel Bayesian heteroskedastic Markov-switching structural vector autoregression with data-driven time-varying identification. The model selects among alternative patterns of exclusion restrictions to identify structural shocks within th...
arxiv.org/abs/hep-ex/0501024v1
The LUCIAE model predictions on the light vector meson production in proton-prot…
The LUCIAE model predictions are compared with experimental data on light vector meson ($ρ,ω,φ$) production in pp, p+Pb and Pb+Pb collisions at 158 A GeV. The model reproduces the general trends of the data, but fails in describing the yield of...