Numeric

Many problems, especially in scientific computing, end up being formulated as matrix operations. This can be anything from PDE-solvers (PDE - Partial Differential Equation) up to image-processing or ML-algorithms. 

Solving Matrix Algebra in JavaScript [An Overview]

Simulations validate the proposed UAV‑CRN optimization algorithm, showing improved rates, convergence, and insights into propulsion power and IT constraints.

Numerical Validation of UAV‑CRN Optimization: Improved Rates Under Energy and PLoS Constraints

Learn how to choose the right numeric data types in MySQL, from integers and decimals to floating-point and bit fields. This guide covers common pitfalls, best 

Navigating MySQL data types: numeric

Simulations show GAR(1) model estimators are consistent and powerful for time series in real, Wasserstein, and SPD matrix spaces.

Numerical Experiments Confirm GAR(1) Model Power in Non-Euclidean Time Series

We evaluate our solvers on three numerical experiments and benchmark them against other nonlinear equation solvers 

How We Evaluated Our Solvers on Three Numerical Experiments and Benchmarked Them

This section introduces the mathematical framework for numerically solving nonlinear problems

Mathematical Description and Numerical Algorithms for Nonlinear Equations

Explore additional experiments on K-SIF and SIF, covering signature depth, noise robustness, and anomaly detection. 

Additional Numerical Experiments on K-SIF and SIF: Depth, Noise, and Discrimination Power

This paper presents a federated learning algorithm using Over-the-Air computation for fairness and robustness, optimizing performance in decentralized networks.

Boosting Fairness and Robustness in Over-the-Air Federated Learning: Numerical Example

Finite difference methods approximate derivatives to simulate market dynamics, offering flexibility and accuracy for option pricing and hedging strategies.

Finite Difference Methods: A Numerical Approach to Option Pricing and Derivatives

This paper presents a novel algorithm using generalized fictitious play to compute mixed equilibria in mean field games with optimal stopping decisions.

Fictitious Play for Mixed Strategy Equilibria in Mean Field Games: Numerical Experiments

Fictitious Play for Mixed Strategy Equilibria in Mean Field Games: Numerical Analysis

A novel algorithm using swarm intelligence to find global Nash equilibria in nonconvex multiplayer games, with convergence guarantees and numerical experiments.

A Consensus-Based Algorithm for Non-Convex Multiplayer Games: Numerical Experiments

Compare the effectiveness of prebunking algorithms in preventing misinformation spread on simulated scale-free networks using the Chung-Lu model


Numerical Analysis of Prebunking Algorithms

In this paper, researchers highlight dataloaders as key to improving ML training, comparing libraries for functionality, usability, and performance.

An Overview of the Data-Loader Landscape: Numerical Results

An Overview of the Data-Loader Landscape: Numerical Results Cont.

Explore the computational analysis and application of Proposition 7.1 in evaluating Ξ12, along with numerical calculations for a detailed understanding.


Numerical Calculation of Ξ12: Detailed Analysis and Findings

This study considers a bivariate jump-diffusion model to describe Bitcoin price dynamics and the number of Google searches affecting the price.

Neural Network for Valuing Bitcoin: Numerical Results, Implementation and Discussion

Our numerical scheme utilizes the GRMHD code KHARMA[1], a performance-portable C++ implementation based on iharm3D; iharm3D is itself an extension of HARM.

The Numerical Methods We Used to Study Black Holes

This article proposes a novel fault diagnosis method: clustering spatially correlated sparse Bayesian learning.

Sparse Bayesian Learning: Numerical Case Studies

This paper presents two neural network approaches that approximate the solutions of static and dynamic conditional optimal transport problems, respectively.

Efficient Neural Network Approaches for Conditional Optimal Transport: Numerical Experiments

Discover the power of Power-Enhancing Residual Networks for superior interpolation in 2D/3D domains with physics-informed solutions, also available on Arxiv.

Physics-Informed with Power-Enhanced Residual Network: Numerical Results

Conformal inference is a fundamental and versatile tool that provides distribution-free guarantees for many machine learning tasks. 

Transductive Conformal Inference With Adaptive Scores: Numerical Bounds and Templates

While software-defined payloads are very promising, their effective utilization requires advanced RRM techniques to optimize resource allocation in real-time.

Supervised Learning Based Real-Time Adaptive Beamforming On-board: Numerical Results

From worst-case bias to variance trade-offs, discover how these algorithms outperform competitors in both empirical and numerical studies. 

Design of Cluster Experiments: Empirical Illustration and Numerical Studies

Numeric is an AI-powered accounting automation platform that helps accounting teams automate recurring month-end close processes, perform technical accounting research, and generate variance explanations.

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NUMERIC

numeric.io

0 emps

Since 2020

Worth 51M

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2017

144.1M

Representing this company? Click here to claim and customize this page!

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