19 results for “topic:fourier-features”
A library of scalable Bayesian generalised linear models with fancy features
Image classification using SVM, KNN, Bayes, Adaboost, Random Forest and CNN.Extracting features and reducting feature dimension using T-SNE, PCA, LDA.
Unofficial pytorch implementation of the paper "Learnable Fourier Features for Multi-Dimensional Spatial Positional Encoding", NeurIPS 2021.
Implementation of two phase field approaches for the surface reconstruction problem. One based of the Modica-Mortola theorem and the other based on Ambrosio-Tortorelli | Master Thesis
Incremental Sparse Spectrum Gaussian Process Regression
Sparse spectrum Gaussian process regression
AG-MAE: Anatomically Guided Spatio-Temporal Masked Auto-Encoder for Online Hand Gesture Recognition
SCFGP: Sparsely Correlated Fourier Features Based Gaussian Process
Multi-Architecture Coupled Ensemble Physics-Informed Neural Networks (MACE-PINN) for solving coupled partial differential equations. Implements parallel subnetworks with Fourier embeddings and adaptive loss weighting for Gray-Scott and Ginzburg-Landau reaction-diffusion systems.
Time series regression modeling on a dataset of supermarket sales across years, with the Darts library in Python.
Forecasting Store Sales for Improved Decision-Making Using Machine Learning for Time Series Data
Tensorflow 2.0 implementation of fourier feature mapping networks.
Neural Fields for Sea Surface Height Interpolation.
O E-COMPRESS é um sistema híbrido de compressão de arquivos que combina redes neurais supervisionadas com técnicas tradicionais como gzip e validação de integridade por CRC e ECC. Ele segmenta arquivos em blocos independentes, codifica cada um com Fourier Features e redes MLP, e reconstrói com alta fidelidade.
Image regression experiments with random fourier feature mapping using PyTorch
An implementation of Fourier feature mapping method using TensorFlow 2.3
This project implements coordinate-based neural networks from scratch in NumPy to reconstruct low- and high-resolution images by mapping 2D pixel coordinates to RGB values. It explores input encoding strategies—none, basic, and Gaussian Fourier features—to evaluate their impact on image quality and detail. Tech: Python (numpy, cv2, os)
A concise introduction and Python implementation of various regression methods, including: Linear, Polynomial, Fourier, Splines, Kernel, GRNN
Visualizing function fittings