Search Results for "benchmark"
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Showing 13 open source projects for "benchmark"
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of an easy-to-use mini-batch loader for many small and single giant graphs, a large number of common benchmark datasets (based on simple interfaces to create your own), and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. We have outsourced a lot of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. ... -
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robosuite
A Modular Simulation Framework and Benchmark for Robot Learning
Robosuite is a modular and extensible simulation framework for robotic manipulation tasks, built on top of MuJoCo. Developed by the ARISE Initiative, Robosuite offers a set of standardized benchmarks and customizable environments designed to advance research in robotic manipulation, control, and imitation learning. It emphasizes realistic simulations and ease of use for both single-task and multi-task learning. -
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PyTorch Geometric Temporal
Spatiotemporal Signal Processing with Neural Machine Learning Models
...Moreover, it comes with an easy-to-use dataset loader, train-test splitter and temporal snaphot iterator for dynamic and temporal graphs. The framework naturally provides GPU support. It also comes with a number of benchmark datasets from the epidemiological forecasting, sharing economy, energy production and web traffic management domains. Finally, you can also create your own datasets. The package interfaces well with Pytorch Lightning which allows training on CPUs, single and multiple GPUs out-of-the-box. PyTorch Geometric Temporal makes implementing Dynamic and Temporal Graph Neural Networks quite easy - see the accompanying tutorial. ... -
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NAVAL-SEM
Free offline SEM software with HTMT, bootstrapping & exports
NAVAL-SEM is a free, open-source, fully offline desktop application for Structural Equation Modeling (SEM), supporting both PLS-SEM and CB-SEM workflows. Designed for researchers, PhD scholars, professors, students, and analysts, it enables advanced quantitative research without subscriptions, cloud dependencies, or proprietary software restrictions. Key features include visual drag-and-drop model building, bootstrapping, mediation analysis, HTMT, AVE, Composite Reliability (CR),... -
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PI-Based Image Encoder / Converter
Python code able to convert / compress image to PI (3.14, π) Indexes
...Features high-performance Numba-accelerated search and a signature 'film-grain' aesthetic upon reconstruction. ZIP also include 16 MB file with 16,7 mil numbers of PI Benchmark(Single-Thread): Hardware & Environment Apple Silicon: Apple M2 (Mac mini/MacBook) x86_64 Platform: Intel Core Ultra 5 225F (Arrow Lake, 10 Cores) OS 1: Fedora 43 (GNOME) OS 2: Windows 11 Pro (23H2/24H2) Software: Python 3.14.3 + Numba JIT (latest) Results (Lower is better) Platform / OS CPU Time (Seconds) macOS (Native) Apple M2 52.151311 s (in default setup) Fedora Linux Intel Core Ultra 5 225F 58.536457 s (in default Power Management: Balanced) Windows 11 Intel Core Ultra 5 225F 59.681427 s (important! ... -
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aioulinux
Linux for Arduino and Makers developers
Hello, I'm the Aioulinux founder, eager to professionally revive the project. Since 2018, the demand for an IoT and Arduino-tailored environment has been evident. Seeking partners for a 2024 version targeting schools and IoT companies, aiming for a secure and comprehensive platform. If you share this vision and wish to collaborate, reach out. Let's revive Aioulinux stronger than ever! Now seeking partners: Live Distro Specialist: Expert in live distributions to ensure... -
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MoCObench
Benchmark instances for multiobjective combinatorial optimization
Benchmark instances for multiobjective combinatorial optimization -
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ARDEN
Specificity Control for Read Alignments Using an Artificial Reference
We introduce ARDEN (Artificial Reference Driven Estimation of false positives in NGS data), a novel benchmark that estimates error rates based on real experimental reads and an additionally generated artificial reference genome. It allows the computation of error rates specifically for a dataset and the construction of a ROC-curve. Thereby, it can be used to optimize parameters for read mappers, to select read mappers for a specific problem or also to filter alignments based on quality estimation. -
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This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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OpenMie aims to solve electromagnetic scattering problems via the Mie method to provide a benchmark against which to test more general scattering codes. Complete field solutions are given for a number of practical geometries.
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sarface is a user-interface to the sysstat/sar database which inputs data from sar and plots to a live X11 graph via gnuplot. It mimics the cmd-line options from sar but can cross-plot any two or more stats and apply simple mathematical functions them.
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Graphical or terminal-based stopwatch with many user-named lap timers. Save / restore timing results via CSV file; timer "runs" even when application isn't running! Supports lap timer label templates. Hildonized (i.e., also runs on Maemo / Nokia 770).
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A benchmarking utility providing administration of the benchmarking procedure and a web interface for public access on the results. The goal is to have an automated procedure after the benchmark specification.
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