PySVM : A NumPy implementation of SVM based on SMO algorithm. Numpy构建SVM分类、回归与单分类，支持缓存机制与随机傅里叶特征
Johnson-Lindenstrauss transform (JLT), random projections (RP), fast Johnson-Lindenstrauss transform (FJLT), and randomized Hadamard transform (RHT) in python 3.x
Localize and track a moving target in a wireless sensor network from RSSI — SVM and Random Fourier Features regression, refined with a Kalman filter.
GRB triangulation via non-stationary time-series models
Efficient approximate Bayesian machine learning
A time-delayed light curve simulation code for GRB location triangulation via random Fourier features.
Incremental Sparse Spectrum Gaussian Process Regression
Official implementation of PromptSplit: kernel-based framework to detect prompt-level disagreements in generative models (text-to-image, LLMs). Identifies divergent prompt clusters via tensor embeddings & random projections for scalability.
We present anomaly detection model that combines the strong statistical foundation of density-estimation-based anomaly detection methods with the representation-learning ability of deep-learning models. The method combines an autoencoder, for learning a low-dimensional representation of the data, with a density-estimation model based on RFF
The official implementation of Randomly Weighted Feature Network for Visual Relationship Detection Tasks (CLeaR@AAAI2022)
[Pattern Recognition 2023] End-to-end Kernel Learning via Generative Random Fourier Features
[AISTATS 2023] Error Estimation for Random Fourier Features
Python implementation of the paper Random Fourier Features based SLAM (https://arxiv.org/pdf/2011.00594.pdf)
Kernel Density Estimation (KDE) is a powerful non-parametric method to estimate continuous probability density functions from data. However, traditional KDE scales poorly with dataset size since it requires the full dataset at prediction time. This repository provides a computationally efficient alternative that approximates KDE with RFF
The official implementation of Randomly Weighted Feature Network for Visual Relationship Detection Tasks (CLeaR@AAAI2022)
Bayesian inference using sparse gaussian processes from tinygp. Examples include 1D and 2D implementation.
Advanced Image Enhancement and Data Recovery: Superresolution Techniques and Missing Data Handling
Holographic computing on FHRR hypervectors — data structures, splat scenes, learning, rendering, CRDT sync, superposed in one complex vector
Eigenvalues & AI, Quantum Physics, Emergence — interactive math blog with React visualizations, KRR Chat demo, and KaTeX. DE+EN at ki-mathias.de
PyTorch Random Fourier Features classifier for white wine quality prediction with 3-class and binary experiments.
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