Popular GitHub Repositories for Reduced Basis

open Multiple View Geometry library. Basis for 3D computer vision and Structure from Motion.

Keras/Pytorch implementation of N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.

Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)

Repository for the Universal Differential Equations for Scientific Machine Learning paper, describing a computational basis for high performance SciML

Data-driven model reduction library with an emphasis on large scale parallelism and linear subspace methods

Smart Algorithms to predict buying and selling of stocks on the basis of Mutual Funds Analysis, Stock Trends Analysis and Prediction, Portfolio Risk Factor, Stock and Finance Market News Sentiment Analysis and Selling profit ratio. Project developed as a part of NSE-FutureTech-Hackathon 2018, Mumbai. Team : Semicolon

Include Basis-MelGAN, MelGAN, HifiGAN and Multiband-HifiGAN, maybe NHV in the future.

本次开源为DL-B，是一个基于ChatGLM、Wav2Lip、So-VITS组建的数字形象方案。可以在此基础之上增加其他组件达到数字生命的效果。This open source is DL-B, which is a digital image scheme based on ChatGLM, Wav2Lip and So-VITS. On this basis, other components can be added to achieve the effect of digital life.

Code for NOLA, an implementation of "nola: Compressing LoRA using Linear Combination of Random Basis"

Hrrformer: A Neuro-symbolic Self-attention Model (ICML23)

Pytorch RBF Layer implements a radial basis function layer in Pytorch. Radial Basis networks can be used to approximate functions.

Approximate Nearest Neighbor search using reduced-rank regression, with extremely fast queries, tiny memory usage, and rapid indexing on modern vector embeddings.

AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)

Federated learning with PyTorch (federated averaging and consensus optimization): with 'reduced' bandwidth

The basic idea is to utilize a U-Net, modified perceptual loss (pearson instead of MAE), learned basis functions, and "mean teacher" training in order to synthesize images of high quality without the normal troubles of training a GAN.

an implementation of a Radial Basis Function Neural Network (RBFNN) for classification problem.

Dimension reduced surrogate construction for parametric PDE maps

GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural Networks

Fine-tuned BERT on SQuAd 2.0 Dataset. Applied Knowledge Distillation (KD) and fine-tuned DistilBERT (student) using BERT as the teacher model. Reduced the size of the original BERT by 40%.

?? Hubness reduced nearest neighbor search for entity alignment with knowledge graph embeddings