531 skills found · Page 3 of 18
maxpumperla / Entropy MdlpMinimum description length principle algorithm in Python, for optimal binning of continuous variables
juangamella / GesPython implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search" by David Maxwell Chickering.
vivienseguy / Large Scale OTStochastic algorithms for computing Regularized Optimal Transport
mirkovicdev / CLUSTERING MARKET REGIMESPython implementation of "Clustering Market Regimes Using the Wasserstein Distance" (Horvath et al., 2021). Detects bull/bear market regimes using optimal transport distance on return distributions. Includes WK-means algorithm, synthetic data generators, and validation metrics. Reproduces paper results on SPY data.
MilanPecov / 15 Puzzle SolversThis project solves the classic 15-puzzle using A* and Breadth First algorithms, implemented in Python. It features a combined heuristic of Manhattan Distance, Linear Conflict, and Walking Distance for optimal performance and includes a user-friendly graphical interface to visualize the solution
Yvaine-Zhang / Models For Intraday Trading Volume PredictionHaving effective intraday forecast for the level of trading volume is of vital importance to algorithmic trading and portfolio management since it attempts to minimize transaction costs by optimally scheduling and placing. The purpose of this project is to create dynamic statistical models of intraday trading volume prediction (in Python). By assuming the stable U shape distribution of intraday trading volume, we apply Deterministic blend, Lognormal Bayesian, Kalman filter and ARIMA model to estimate and generate out of sample forecast on 12 US equity sector ETFs. Results show that some of the proposed methods are able to obviously outperform common volume forecasting methods.
adler-1994 / Gmclgmcl, which stands for general monte carlo localization,is a probabilistic-based localization technique for mobile robots in 2D-known map. It integrates the adaptive monte carlo localization - amcl - approach with 3 particle filter algorithms (Optimal, Intelligent,Self-adaptive) to improve the performance of amcl while working in real time........Main node structure and amcl-algorithms’s code was derived, with thanks, from Brian Gerkey's amcl package.
chadogome / OptimalOBBOptimal Oriented Bounding Boxes algorithms
InvestmentSystems / RecombinatorRecombinator is a Python package for statistical resampling in Python. It provides various algorithms for the iid bootstrap, the block bootstrap, as well as optimal block-length selection.
sharma-subendra-kr / LimberGridViewLimberGridView, a powerful JavaScript Library using Computational Geometry to render movable, resizable, and auto-arranging grids. Written in vanilla JavaScript, it can be plugged into most frameworks, plus it has a plugin for React applications. It gives users the most optimal arrangements using its highly efficient and fine-tuned algorithm.
aliasgharheidaricom / Slime Mould Algorithm A New Method For Stochastic Optimization In this paper, a new stochastic optimizer, which is called slime mould algorithm (SMA), is proposed based upon the oscillation mode of slime mould in nature. The proposed SMA has several new features with a unique mathematical model that uses adaptive weights to simulate the process of producing positive and negative feedback of the propagation wave of slime mould based on bio-oscillator to form the optimal path for connecting food with excellent exploratory ability and exploitation propensity. The proposed SMA is compared with up-to-date metaheuristics in an extensive set of benchmarks to verify the efficiency. Moreover, four classical engineering structure problems are utilized to estimate the efficacy of the algorithm in optimizing engineering problems. The results demonstrate that the algorithm proposed benefits from competitive, often outstanding performance on different search landscapes. The source codes and info of SMA are publicly available at: http://www.alimirjalili.com/SMA.html
downflux / Go OrcaGolang implementation of the Optimal Reciprocal Collision Avoidance (ORCA) algorithm
AdrianSeguraOrtiz / GENECISoftware package whose main functionality consists of an evolutionary algorithm to determine the optimal ensemble of machine learning techniques for genetic network inference based on the confidence levels and topological characteristics of its results.
Rucknium / OSPEADOptimal Static Parametric Estimation of Arbitrary Distributions (OSPEAD) for the Monero decoy selection algorithm
AkshayS21 / Reinforcement Learning For Optimal Financial TradingImplementation of the DDPG algorithm for Optimal Finance Trading
k2cu8 / PyOMTA PyTorch implementation of adaptive Monte Carlo Optimal Transport algorithm
analyticalmonk / KMeans ElbowCode for determining optimal number of clusters for K-means algorithm using the 'elbow criterion'
liubin06 / BNSBayesian negative sampling is the theoretically optimal negative sampling algorithm that runs in linear time.
kbmajeed / Exposure FusionExposure fusion is a technique that creates a single image with optimal detail from a set of multi-exposed images. As developed by Tom Mertens et al., the proposed algorithm computes relevant quality measures; Contrast, Saturation, and Well-Exposedness. These measures are then combined to create a weight map used to blend each of the multi-exposed images to a single image with best exposure.
sandeepsripada / SummarizationPerforms multi document summarization. Includes a method to generate summaries: The method uses a sentence importance score calculator based on various semantic features and a semantic similarity score to select sentences that would be most representative of the document. It uses stack-decoder algorithm as used as a template and builds on it to produce summaries that are closer to optimal.
