Search Results for "automatic1111-stable-diffusion" - Page 5

Neuroimitator project.

pySTEP or Python Strongly Typed gEnetic Programming: A light Genetic Programming API that allows the user to easily evolve populations of trees with precise grammatical and structural constraints.

TreeLiker is a collection of fast algorithms for working with complex structured data in relational form. The data can, for example, describe large organic molecules such as proteins or groups of individuals such as social networks or predator-prey networks etc. The algorithms included in TreeLiker are unique in that, in principle, they are able to search given sets of relational patterns exhaustively, thus guaranteeing that if some good pattern capturing an important feature of the problem...

EpochX is an open source genetic programming framework, specifically for analysing the properties of evolutionary automatic programming. It supports 3 popular representations - Strongly-Typed GP, Context-Free Grammar GP and Grammatical Evolution.

P53 Cancer Rescue Project, University of California, Irvine , Samuel A. Danziger, Christopher Wassman, Faezeh Salehi Amiri, Roberta Baronio, Linda Hall, Rainer K. Brachmann, G. Wesley Hatfield, Peter Kaiser, Richard H. Lathrop

CRFSharp(aka CRF#) is a .NET(C#) implementation of Conditional Random Fields, an machine learning algorithm for learning from labeled sequences of examples. It is widely used in Natural Language Process (NLP) tasks, for example: word breaker, postagging, named entity recognized, query chunking and so on. CRF#'s mainly algorithm is the same as CRF++ written by Taku Kudo. It encodes model parameters by L-BFGS. Moreover, it has many significant improvement than CRF++, such as totally...

This program runs on a laptop with a wireless card. It scan for wireless access points (WAPs) and notes their Base Station ID or BSSID and their Received Signal Strength Indicator or RSSI. This data, along with an identifier for the physical location or 'ROOM', and the name of the computer it is being run on are stored as an ARFF file, which is compatible with programs such as WEKA and RAPIDMINER.

mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3. mlpy is available both for Python >=2.6 and Python 3.X.

This project contains weka packages of neural networks algorithms implementations like Learning Vector Quantizer (LVQ) and Self-organizing Maps (SOM). For more information about weka, please visit http://www.cs.waikato.ac.nz/~ml/weka/

HSSVM(Hyper-Sphere Support Vector Machines) is a software for solving multi-classification problem, implemented by Java.

R-Portfolio - breakeven optimally diversified investment portfolio. Оптимально диверсифицированный инвестиционный портфель.

SVM# is a svm(support vector machine) classification implemented in C#. The project contains both train and predict modules.

RoboBeans is an interface to the "Robocup 2D Soccer Simulation Server" that allows developers to write Robocup teams\agents concentrating on behaviour and AI without having to worry about syntax of communication or network issues.

Feating constructs a classification ensemble comprising a set of local models. It is effective at reducing the error of both stable and unstable learners, including SVM. For details see the paper at http://dx.doi.org/10.1007/s10994-010-5224-5.

An information extraction library implementing modern algorithms for the extraction of named entities from text.

The aim of ALIVE is to develop new approaches to the engineering of flexible, adaptable distributed service-oriented systems based on the adaptation of social coordination and organisation mechanisms.

.NET library for embedding CLIPS in to .NET applications.

The TreeRank project is a R package implementing a Machine Learning algorithm to build tree-based ranking rules from data with binary labels, based on ROC optimization.

The data complexity library, DCoL, is a machine learning software that implements all metrics to characterize the apparent complexity of classification problems. The code is implemented in C++ and can be run on multiple platforms.

Content Addressable Memory, Multi-Variate Statistics, Data Mining Includes analyzing datasets, extracting patterns, creating empirical expert system. Computes joint probabilities and implements a "belief" as the solution of an equilibrium equation

An adaptive neural network and evolutionary algorithms approach to the machine learning tasks, based on the modular graph grammars. Tested on the "two spirals problem" and other tasks. Implemented in Matlab and C++.

This e-book is devoted to global optimization algorithms, which are methods to find optimal solutions for given problems. It focuses on Evolutionary Computation but also discusses other apporaches like Simulated Annealing and Extremal Optimization.

The STAIR Vision Library (SVL), originally developed to support the STanford AI Robot, provides software infrastructure for computer vision, machine learning, and probabilistic graphical models.

Moara is a biological text mining tool and consists of a Java library and some auxiliary MySQL databases for gene/protein training and extraction of mentions and its further normalization and disambiguation.

Program to performing the complete cycle of neural networks analysis: preparing data, choosing neural network (CasCor, MP, LogRegression, PNN), learning of network, monitoring learning state, ROC-analysis, optimization of network parameters using GA.