Search Results for "lepton-optimizer" - Page 2

...The package can address continuous objectives, constrained problems, and combinatorial tasks such as the traveling salesman problem. A consistent workflow lets users define an objective, configure an optimizer, run iterations, and inspect the best solution. Genetic algorithm operators can be replaced through user-defined functions or subclassing. Runs may continue from earlier iterations instead of restarting. Vectorization, threading, multiprocessing, caching, examples, and plotting support help users experiment with performance and convergence.

SimSiam is a PyTorch implementation of “Exploring Simple Siamese Representation Learning” by Xinlei Chen and Kaiming He. The project introduces a minimalist approach to self-supervised learning that avoids negative pairs, momentum encoders, or large memory banks—key complexities of prior contrastive methods. SimSiam learns image representations by maximizing similarity between two augmented views of the same image through a Siamese neural network with a stop-gradient operation, preventing...

...Something sweet built with Tensorflow and Pytorch(coming soon). Load your data, your data must be in a text format. Download the example data from the example folder. Tune your model to know the best optimizer, activation method to use.

Linux-intelligent-ocr-solution Lios is a free and open source software for converting print in to text using either scanner or a camera, It can also produce text out of scanned images from other sources such as Pdf, Image, Folder containing Images or screenshot. Program is given total accessibility for visually impaired. A Tesseract Trainer GUI is also shipped with this package. Forum : https://groups.google.com/forum/#!forum/lios Video Tutorial :...

Physiologically based toxicokinetic (PBTK) modeling offers great promise in environmental risk assessment, potentially speeding up dose-response studies while minimizing animal testing. Some limitations exist in the PBTK field, such as difficulty of model development and a lack of application specific software tools to help modelers. Some parameters used in PBTK models, such as tissue weights, are easily measure. Other parameters can be determined through in-vitro experiments or through...

...The repository provides code for training and evaluating learned optimizers that can generalize across different problem types, such as quadratic functions and image classification tasks (MNIST and CIFAR-10). Using TensorFlow, it defines a meta-optimizer model that learns by observing and adapting to the optimization trajectories of other models. The project allows users to compare performance between traditional optimizers and the learned optimizer (L2L) on various benchmarks, demonstrating how optimization strategies can be learned through experience. The design supports both single-variable and high-dimensional problems, and includes tools for evaluating how well a learned optimizer performs on unseen tasks.

name: leap frog optimizer version: 0.5 ALPHA author: Mark Redd email: redddogjr@gmail.com written for python version: 2 optimizer algorithm website: http://www.r3eda.com/ about: This optimizer was written based on the algorithm published by Dr. R. Russell Rhinehart. A full explanation of the algorithm can be found at the following URL: http://www.r3eda.com/leapfrogging-optimization-algorithm/ The following are "key references" published on the optimization website explaining the technique: - Rhinehart, R. ...

...By leveraging SMT (Satisfiability Modulo Theories) solvers, Souper symbolically analyzes LLVM Intermediate Representation (IR) to synthesize equivalent, more efficient expressions. It identifies peephole optimizations—small instruction-level improvements—that LLVM’s optimizer may overlook, thereby improving compiled code quality. Souper can operate in multiple modes: as a standalone analysis tool that extracts and solves SMT queries from LLVM bitcode, or as an LLVM optimization pass that applies discovered optimizations directly to the IR. It integrates seamlessly with Clang and LLVM tools and supports caching mechanisms (RAM or Redis) to accelerate repeated analyses. ...

Portfolio Optimizer Software. Automatically calculates the best asset combination for a given portfolio, expected return, risk and Sharpe ratio. Performs Monte Carlo simulation of thousands of different portfolios.

Protein ALignment Optimiser (PALO) is a script for the selection and alignment of the best combination of transcripts among orthologous genes. PALO is mainly written in Python, although other programming languages are also implemented (R, Perl...).

Entirely source-based system. The goal is to provide extremely flexible but easy-to-compile Linux-like OS ready for SSI clusters. Installation procedure is network-independent and automated.

The Library Optimizer tool rebuilds shared libraries to contain only the object files needed to provide symbols required by executables and shared libraries in a given directory tree. It can be used to reduce file system sizes for embedded systems.