AaltoML/nonstationary-audio-gp

Stars
11
Rank 1,694,829 (Top 34 %)
Language
MATLAB
License
Apache License 2.0
Created over 5 years ago
Updated over 5 years ago

AaltoML/nonstationary-audio-gp

AaltoML

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

End-to-End Probabilistic Inference for Nonstationary Audio Analysis

BayesNewton

Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.

SDE

Example codes for the book Applied Stochastic Differential Equations

kalman-jax

Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX

Jupyter Notebook

GP-MVS

Multi-View Stereo by Temporal Nonparametric Fusion

vio_benchmark

Tools for benchmarking different Visual-Inertial Odometry solutions

generative-inverse-heat-dissipation

Code release for the paper Generative Modeling With Inverse Heat Dissipation

spatio-temporal-GPs

Code for NeurIPS 2021 paper 'Spatio-Temporal Variational Gaussian Processes'

android-viotester

Visual-Inertial Odometry (VIO) benchmark app for Android

IHGP

Infinite-horizon Gaussian processes

boundary-gp

Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features

Jupyter Notebook

mobile-cv-suite

A Computer Vision & real-time ML resarch library for mobile phones. The building blocks required to test new algorithms on mobile & embedded devices.

SLAM-module

PeriodicBNN

Code for 'Periodic Activation Functions Induce Stationarity' (NeurIPS 2021)

Jupyter Notebook

uncertainty-nerf-gs

Code release for the paper "Sources of Uncertainty in 3D Scene Reconstruction"

hilbert-gp

Codes for Hilbert space reduced-rank GP regression

scalable-inference-in-sdes

Methods and experiments for assumed density SDE approximations

Jupyter Notebook

sequential-gp

Code for 'Memory-based dual Gaussian processes for sequential learning' (ICML 2023)

Jupyter Notebook

stationary-activations

Codes for 'Stationary Activations for Uncertainty Calibration in Deep Learning' (NeurIPS 2020)

Jupyter Notebook

t-SVGP

Codes for 'Dual Parameterization of Sparse Variational Gaussian Processes' (NeurIPS 2021)

sfr

PyTorch implementation of Sparse Function-space Representation of Neural Networks

Jupyter Notebook

iterative-smoothing-bridge

Code for 'Transport with Support: Data-Conditional Diffusion Bridges'

zed-capture

Tool for capturing IMU sensor and video data through zed-open-capture

calibrated-dnn

Repository containing code for the paper: Fixing Overconfidence in Dynamic Neural Networks

accelerated-arrays

Lightweight accelerated tensor / array programming library for smart phone GPUs

view-aware-inference

Gaussian Process Priors for View-Aware Inference

u-blox-capture

apml

Advances in Probabilistic Machine Learning Seminar

improved-hyperparameter-learning

Codes for 'Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models' (ICML 2023)

Jupyter Notebook

sfr-experiments

Code accompanying ICLR 2024 paper "Function-space Parameterization of Neural Networks for Sequential Learning"

Jupyter Notebook