Search Results for "norm"
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Showing 30 open source projects for "norm"
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llm-abliteration
Make abliterated models with transformers, easy and fast
...Batch inference and quantized model loading help reduce processing requirements. Sharded weight modifications allow larger models to be processed with limited memory. Advanced options include norm-preserving transformations, directional projection, and configurable layer strategies. Modified models can be tested and compared, although refusal removal is not guaranteed. -
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MNE-Python
Magnetoencephalography (MEG) and Electroencephalography EEG in Python
Open-source Python package for exploring, visualizing, and analyzing human neurophysiological data. MNE-Python is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, statistics, and more. -
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Pathway
Python ETL framework for stream processing, real-time analytics, LLM
...Pathway is especially well-suited for scenarios like financial analytics, IoT, fraud detection, and logistics, where high-velocity and continuously changing data is the norm. Unlike traditional batch processing frameworks, Pathway continuously updates the results of your data logic as new events arrive, functioning more like a database that reacts in real-time. It supports Python, integrates with modern data tools, and offers a deterministic dataflow model to ensure reproducibility and correctness. -
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HCubature.jl
Pure-Julia multidimensional h-adaptive integration
The HCubature module is a pure-Julia implementation of multidimensional "h-adaptive" integration. then hcubature(f, a, b) computes the integral, adaptively subdividing the integration volume into smaller and smaller pieces until convergence is achieved to the desired tolerance (specified by optional rtol and atol keyword arguments. Because hcubature is written purely in Julia, the integrand f(x) can return any vector-like object (technically, any type supporting +, -, * real, and norm: a Banach space). You can integrate real, complex, and matrix-valued integrands, for example. Note that HCubature assumes that your function f(x) can be computed at arbitrary points in the integration domain. (This is the ideal way to do numerical integration.) If you instead have f(x) precomputed at a fixed set of points, such as a Cartesian grid, you will need to use some other method (e.g. ... -
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Convex.jl
A Julia package for disciplined convex programming
...Convex.jl makes it easy to describe optimization problems in a natural, mathematical syntax, and to solve those problems using a variety of different (commercial and open-source) solvers. Convex.jl works by transforming the problem—which possibly has nonsmooth, nonlinear constructions like the nuclear norm, the log determinant, and so forth—into a linear optimization problem subject to conic constraints. This reformulation often involves adding auxiliary variables and is called an "extended formulation", since the original problem has been extended with additional variables. These formulations rely on the problem being modeled by combining Convex.jl's "atoms" or primitives according to certain rules which ensure convexity, called the disciplined convex programming (DCP) ruleset. ... -
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Coolify
An open-source & self-hostable Heroku / Netlify / Vercel alternative
Coolify is an open-source & self-hostable alternative to Heroku / Netlify / Vercel / etc. It helps you manage your servers, applications, and databases on your own hardware; you only need an SSH connection. You can manage VPS, Bare Metal, Raspberry PIs, and anything else. Imagine having the ease of a cloud but with your own servers. That is Coolify. No vendor lock-in, which means that all the configurations for your applications/databases/etc are saved to your server. So, if you decide to... -
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Bootstrap Your Own Latent (BYOL)
Usable Implementation of "Bootstrap Your Own Latent" self-supervised
...This repository offers a module that one can easily wrap any image-based neural network (residual network, discriminator, policy network) to immediately start benefitting from unlabelled image data. There is now new evidence that batch normalization is key to making this technique work well. A new paper has successfully replaced batch norm with group norm + weight standardization, refuting that batch statistics are needed for BYOL to work. Simply plugin your neural network, specifying (1) the image dimensions as well as (2) the name (or index) of the hidden layer, whose output is used as the latent representation used for self-supervised training. -
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librsb
A shared memory parallel sparse matrix library including Sparse BLAS.
...The most common operations necessary to iterative solvers are available, e.g.: matrix-vector multiplication, triangular solution, rows/columns scaling, diagonal extraction / setting, blocks extraction, norm computation, formats conversion. The RSB format is especially well suited for symmetric and transposed multiplication variants. On these variants, librsb has been found to be faster than Intel MKL's implementation for CSR. Most numerical kernels code is auto generated, and the supported numerical types can be chosen by the user at build time. ... -
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DeepSeek LLM
DeepSeek LLM: Let there be answers
...The model is trained from scratch, reportedly on a vast multilingual + code + reasoning dataset, and competes with other open or open-weight models. The architecture mirrors established decoder-only transformer families: pre-norm structure, rotational embeddings (RoPE), grouped query attention (GQA), and mixing in languages and tasks. It supports both “Base” (foundation model) and “Chat” (instruction / conversation tuned) variants. -
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ProxSDP.jl
Semidefinite programming optimization solver
ProxSDP is an open-source semidefinite programming (SDP) solver based on the paper "Exploiting Low-Rank Structure in Semidefinite Programming by Approximate Operator Splitting". The main advantage of ProxSDP over other state-of-the-art solvers is the ability to exploit the low-rank structure inherent to several SDP problems. -
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Detectron2
Next-generation platform for object detection and segmentation
Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up rewrite of the previous version, Detectron, and it originates from maskrcnn-benchmark. It is powered by the PyTorch deep learning framework. Includes more features such as panoptic segmentation, Densepose, Cascade R-CNN, rotated bounding boxes, PointRend, DeepLab, etc. Can be used as a library to support different projects on top of it. We'll... -
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RMGDFT
Real Space Multigrid based electronic structure code.
News: active RMG development has moved to github https://github.com/RMGDFT News: V4.1.0 released on 09/29/2020 News: V4.0.0 released on 09/01/2020 with major updates. News: V3.0.0 released on 06/09/2018 with major updates. News: V2.2.2 released on 10/14/2017 with minor bug fixes. News: V2.2 with performance enhancements, bug fixes and new features released on 06/26/2017. Sources are available with binaries to follow soon. News: V2.1 with many improvements released on... -
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xrechnung-visualization-codelist-resolve
Resolving codelists for XRechnung-Visualization
Mit den im GitHub Repositorium der KoSIT bereitgestellten XSL Transformatoren (https://github.com/itplr-kosit/xrechnung-visualization) kann eine elektronische Rechnung gem. der Europäischen Norm EN16931 sowie davon abgeleitete CIUS, wie z.B. XRechnung, in eine HTML- oder PDF-Ansicht überführt werden. Mit den hier bereitgestellten Skripten kann innerhalb dieser XSL Transformation zusätzlich zu den enthaltenen Codelistenwerten eine Beschreibung des jeweiligen Codelistenwertes ergänzt werden. Die originalen Codewerte werden dazu nicht verändert, sondern die Beschreibung lediglich in Klammer ergänzt. ... -
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DaNNet
Deep Artificial Neural Network framework using Armadillo
DaNNet is a C++ deep neural network library using the Armadillo library as a base. It is intended to be a small and easy to use framework with no other dependencies than Armadillo. It uses independent layer-wise optimization giving you full flexibility to train your network. -
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NNC
Nuclear Norm Clustering
We present Nuclear Norm Clustering (NNC), an algorithm that can be used in different fields as a promising alternative to the k-means clustering method, and that is less sensitive to outliers. The NNC algorithm requires users to provide a data matrix M and a desired number of cluster K. We employed simulate annealing techniques to choose an optimal L that minimizes NN(L). -
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L1-norm-robust-regression
linear regression on the basis of minimal absolute deviations error
This software provides a Fortran95 implemented routine to call and obtain the L1-norm regression coefficients. The "standard" linear regression minimizes the squared error. (L2-norm-regression). It allows for a simple solution process, hence its popularity. But it is not robust to outlier points. L1-norm regression is robust with respect to outliers but the solution algorithm is more difficult. It minimizes the sum of absolute deviations. -
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dnrDALMAS
A general-level Prolog implementation of the DALMAS architecture.
...University of Gävle, Division of Computer Science; University of Gävle. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-1475 See also: Odelstad, J., & Boman, M. (2004). Algebras for Agent Norm-Regulation. Annals of Mathematics and Artificial Intelligence, 42(1), 141–166. http://doi.org/10.1023/B:AMAI.0000034525.49481.4a -
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pyL1min
General purpose norm-1 minimization solver in Python
pyL1min is a general purpose norm-1 (l1) minimization solver written in Python. It is based on NumPy/SciPy, CVXOPT ( FFTW enabled) to solve l1 minimization problems that are based on interior point methods. You need to install Python, NumPy/SciPy and CVXOPT ( FFTW enabled) to use this software. The test.py program demonstrates a simple application in Compressive Sensing and shows how to use l1min module. -
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Data Matrix
Java Api to manipulate simple on data of Matrix Type
...Usefull methods to manipulate with diagonals. For example you can create block diagonal matrix. There is lot of usefull methods to manipulate on mathematic matrix also, like determinant , norm , minor , cofactor , solveLienarSystem , arithmetic operations also and lot more. -
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2OPL
2OPL is a norm programming language for agent organizations.
...Effect rules describe how actions change the brute facts. Norms describe which environment states counts as violations. Finally sanction rules can be programmed to respond to norm violations. The current implementation is based on logic programming (Prolog in particular). For those users who are not familiar with Prolog we advise the free ebook Learn Prolog Now (http://www.learnprolognow.org). The interpreter supports three different norm specifications. For more information see the documentation or mail one of the developers. -
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Stochastic gradient boosting
A java implementation of the stochastic gradient boosting method
Stochastic gradient boosting method using trees is flexible without sacrificing fitting performance in general. The method can be applied to either categorical data or quantitative data. The current Java implementation uses the L2 norm loss function, which is suitable for the general regression task. -
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OpenDinTest is a OpenOffice-Calc-Sheet for statistical Data-Analysis according to the german industry-norm DIN 32645. <br> <br> OpenDinTest ist eine OpenOffice-Calc-Datei zur statistischen Auswertung von Messdaten nach der DIN 32645. <br>
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Fuzzy controller that works PLC Siemens s226 and variable-frequency conversor Siemens m440. This system works with feedback from sensor encoder and the norm IEC-61131-7.
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Java Matrix object. Thread safe with deadlock avoidance. Matrix Multiply, Add, Subtract, Cross product, Dot Product, norm, normalize, angle between vectors and MANY data manipulation functions. This would make a great graphics addin...
