Search Results for "structural"
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Showing 45 open source projects for "structural"
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Total Network Visibility for Network Engineers and IT ManagersThis means every device on your network, and every interface on every device is automatically analyzed for performance, errors, QoS, and configuration.
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Qwen-Image-Layered
Qwen-Image-Layered: Layered Decomposition for Inherent Editablity
...This architecture allows richer semantic interpretation, enabling use cases such as scene decomposition, object-level editing, layered captioning, and more fine-grained multimodal reasoning than with flat image encodings alone. By combining text and structured image representations, it aims to facilitate tasks where both descriptive and structural understanding are important, such as detailed image QA, interactive image editing via prompt layers, and image-conditioned generation with structural control. The layered approach supports training signals that help the model learn how visual elements relate to each other and to textual context, rather than simply learning global image embeddings. -
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AlphaFold 3
AlphaFold 3 inference pipeline
...This repository provides the complete inference pipeline for running AlphaFold 3, though access to the model parameters is restricted and must be obtained directly from Google under specific terms of use. The system is designed for scientific research applications in structural biology, biochemistry, and bioinformatics, enabling accurate modeling of proteins, ligands, and covalent modifications. Users can perform local predictions via Docker containers, integrating AlphaFold 3’s inference process with provided JSON input configurations. The software includes flexible options for running both data preprocessing and GPU-accelerated inference, allowing users to adapt to available computational resources. -
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statsmodels
Statsmodels, statistical modeling and econometrics in Python
...Generalized linear models with support for all of the one-parameter exponential family distributions. Markov switching models (MSAR), also known as Hidden Markov Models (HMM). Vector autoregressive models, VAR and structural VAR. Vector error correction model, VECM. Robust linear models with support for several M-estimators. statsmodels supports specifying models using R-style formulas and pandas DataFrames. -
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Protenix
A trainable PyTorch reproduction of AlphaFold 3
Protenix is an open-source, trainable PyTorch reimplementation of AlphaFold 3, developed by ByteDance with the goal of democratizing high-accuracy protein structure prediction for computational biology and drug-discovery research. Protenix provides a complete pipeline for turning protein sequences (with optional MSA / sequence alignment) or structural inputs (e.g. PDB/CIF) into full 3D atomic-level structure predictions. It supports both “full” models and lightweight variants such as “Protenix-Mini,” offering a trade-off between speed/compute cost and predictive accuracy — making structure prediction accessible even in resource-constrained environments. The project also includes support for constraints (e.g., specifying residue- or atom-level contact constraints, or pocket constraints) to guide predictions toward biologically or experimentally relevant conformations, which enhances its utility for tasks like modeling complexes, ligands, or antibody–antigen interactions. -
Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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Penzai
A JAX research toolkit to build, edit, & visualize neural networks
Penzai, developed by Google DeepMind, is a JAX-based library for representing, visualizing, and manipulating neural network models as functional pytree data structures. It is designed to make machine learning research more interpretable and interactive, particularly for tasks like model surgery, ablation studies, architecture debugging, and interpretability research. Unlike conventional neural network libraries, Penzai exposes the full internal structure of models, enabling fine-grained... -
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DGL
Python package built to ease deep learning on graph
...We also want to make the combination of graph based modules and tensor based modules (PyTorch or MXNet) as smooth as possible. DGL provides a powerful graph object that can reside on either CPU or GPU. It bundles structural data as well as features for a better control. We provide a variety of functions for computing with graph objects including efficient and customizable message passing primitives for Graph Neural Networks. -
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Tencent Cloud Code Analysis
Static code analysis
Tencent Cloud Code Analysis (TCA for short, used internally by the R&D code CodeDog ) is a cloud-native, distributed, high-performance comprehensive code analysis and tracking platform that integrates many analysis tools, including server, web and client The three components have integrated a number of self-developed tools, and also support the dynamic integration of analysis tools of various programming languages in the industry. Obtain the Tencent Cloud code analysis platform by... -
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ANYstructure
GUI based steel structure calculation and optimization tool.
GUI based steel optimization tool for naval architects and structural engineers. Calculate and optimize the following: Minimum plate thickness (DNV/DNVGL-OS-C101) Minimum section modulus of stiffener/plate (DNVGL-OS-C101) Minimum shear area (DNVGL-OS-C101) Buckling (DNVGL-RP-C201) Fatigue for plate/stiffener connection (DNVGL-RP-C203) Compartments (tank pressures) are created automatically. -
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FEATool Multiphysics - FEA & CFD Toolbox
FEATool Multiphysics is an easy-to-use FEA and CFD Simulation Toolbox
...With a very easy-to-use GUI, anyone is now able to quickly set up and perform large scale dynamical and complex engineering physics simulations, with coupled fluid flow, heat transfer, structural mechanics, chemical transport, and electromagnetics effects, without having to learn complex programming. In addition to built-in CAD and pre/post-processing, automatic mesh generation, and multi-physics solvers, FEATool also seamlessly integrates the state-of-the-art OpenFOAM [1], SU2, and FEniCS CFD and FEA solvers. Moreover, native itegration with MATLAB and Python allows advanced simulation scripts and programmatic use cases such as in AI and machine learning [2]... -
Empower Your Workforce and Digitize Your Shop FloorEasily connect to most tools and equipment on the shop floor, enabling efficient data collection and boosting productivity with vital insights. Turn information into action to generate new ideas and better processes.
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CAMPARI
Software for molecular simulations and trajectory analysis
We are proud to introduce version 5 of CAMPARI. We have added a number of new features, most notably a Python interface for interpreting user-supplied code (with the help of ForPy), a novel trajectory storage standard (with the help of libpqxx/PostgreSQL), and a module for performing transition path theory. Naturally, CAMPARI continues to provide the reference implementation of the ABSINTH force field paradigm and implicit solvation model. CAMPARI is a joint package for performing and... -
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ControlNet
Let us control diffusion models
ControlNet is a neural network architecture designed to add conditional control to text-to-image diffusion models. Rather than training from scratch, ControlNet “locks” the weights of a pre-trained diffusion model and introduces a parallel trainable branch that learns additional conditions—like edges, depth maps, segmentation, human pose, scribbles, or other guidance signals. This allows the system to control where and how the model should focus during generation, enabling users to steer... -
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CausalNex
A Python library that helps data scientists to infer causation
CausalNex is a Python library that uses Bayesian Networks to combine machine learning and domain expertise for causal reasoning. You can use CausalNex to uncover structural relationships in your data, learn complex distributions, and observe the effect of potential interventions. -
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Hyperformer
Hypergraph Transformer for Skeleton-based Action Recognition
...To relax such a restriction, Self-Attention (SA) mechanism has been adopted to make the topology of GCNs adaptive to the input, resulting in the state-of-the-art hybrid models. Concurrently, attempts with plain Transformers have also been made, but they still lag behind state-of-the-art GCN-based methods due to the lack of structural prior. -
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SBEVSL is a collaborative project between Dowling and RIT on the development of a Structural Biology Extensible Visualization Scripting Language, so that users can move freely among various molecular graphics tools, such as rasmol, pymol, raster3d, etc.
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Karate Club
An API Oriented Open-source Python Framework for Unsupervised Learning
Karate Club is an unsupervised machine learning extension library for NetworkX. Karate Club consists of state-of-the-art methods to do unsupervised learning on graph-structured data. To put it simply it is a Swiss Army knife for small-scale graph mining research. First, it provides network embedding techniques at the node and graph level. Second, it includes a variety of overlapping and non-overlapping community detection methods. Implemented methods cover a wide range of network science... -
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DockStream
A Docking Wrapper to Enhance De Novo Molecular Design
...DockStream is integrated with the de novo design platform, REINVENT, allowing one to incorporate docking into the generative process, thus providing the agent with 3D structural information. -
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AliceMind
ALIbaba's Collection of Encoder-decoders from MinD
This repository provides pre-trained encoder-decoder models and its related optimization techniques developed by Alibaba's MinD (Machine IntelligeNce of Damo) Lab. Pre-trained models for natural language understanding (NLU). We extend BERT to a new model, StructBERT, by incorporating language structures into pre-training. Specifically, we pre-train StructBERT with two auxiliary tasks to make the most of the sequential order of words and sentences, which leverage language structures at the... -
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Frontend Regression Validator (FRED)
Visual regression tool used to compare baseline and updated instances
...FRED is responsible for automatic visual regression testing, with the purpose of ensuring that functionality is not broken by comparing a current(baseline) and an updated version of a website. The visual analysis computes the Normalized Mean Squared error and the Structural Similarity Index on the screenshots of the baseline and updated sites, while the visual AI looks at layout and content changes independently by applying image segmentation Machine Learning techniques to recognize high-level text and image visual structures. This reduces the impact of dynamic content yielding false positives. FRED is designed to be scalable. ... -
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2D Structural Analysis
Determine the bending moments, shear forces, axial forces and displace
2D Structural Analysis in Python by Ritchie Vink A collection examples of 2D Finite Element Analysis (FEA) made with Jupyter Notebook Lab - https://jupyter.org/ To install Jupyter - https://jupyter.org/install ===== App is available on Play Store -> https://play.google.com/store/apps/details?id=com.ulm.struct If you want to download a python editor for your android smartphone follow this link -> https://play.google.com/store/apps/details? -
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Python Patterns
A collection of design patterns/idioms in Python
Python-Patterns is a repository collecting implementations of many classical design patterns and idioms, written in Python. It serves as an educational resource: showing how to implement creational, structural, behavioral, testability, and other patterns in a Pythonic style (or sometimes less so), illustrating trade-offs, different styles, and use cases. It’s intended for learners or developers interested in software architecture or design, rather than as a production library. Includes pattern examples for testability, delegation, flyweight, proxy, etc., plus patterns outside the classical set (registry, specification, etc.) ... -
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TI2BioP allows mainly the calculation of topological indices (spectral moments) derived from inferred and artificial 2D structures of DNA, RNA and proteins being possible to carry out a structure-function correlation irrespective of sequence alignments. TI2BioP version 3.0 is a python platform with a graphical interface designed for Windows, Linux and Mac OS.
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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
...The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction. The repository contains reference code accompanying the research paper node2vec: Scalable Feature Learning for Networks (KDD 2016). It allows researchers and practitioners to apply node2vec to various graph datasets and evaluate embedding quality on downstream tasks. ... -
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PBSuite
Software for Long-Read Sequencing Data from PacBio
...PBJelly fills or reduces as many captured gaps as possible to produce upgraded draft genomes. ----- PBHoney ----- Read The Paper http://www.biomedcentral.com/1471-2105/15/180/abstract PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants. -
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Biskit is a python library for structural bioinformatics research. It simplifies the analysis of macromolecular structures, protein complexes, and molecular dynamics trajectories and offers a platform for the rapid integration of external programs. PLEASE NOTE: The Biskit source code as well as any later releases are now hosted on https://github.com/graik/biskit The sourceforge repo is only kept here for reference.
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Hydroponic Automation Platform (HAPI)
Technologies for automating food production on various scales
The Hydroponic Automation Platform Initiative (HAPI) develops and provides hardware and software components for automating food production using hydroponic, aquaponics, and precision agriculture techniques. High-yield production in urban settings is one of the primary goals. Artifacts include hardware design (mainly Arduino-based), firmware, management software and reporting modules.
