ebonilla

bayes_dag

Project Implemeting BayesDag of Annadani et al

ebonilla.github.io

My Personal Website

Differentiable-DAG-Sampling

Differentiable DAG Sampling (ICLR 2022)

FFVD

Code repository for Free-Form Variational Inference for Gaussian Process State-Space Models (ICML-2023)

softsort

Code for "SoftSort: A Continuous Relaxation for the argsort Operator", ICML 2020.

releasing-research-code

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

ebonilla.github.old.io

My Home Page

GPt

Gaussian Processes for Sequential Data

starter-hugo-academic

🎓 Hugo Academic Theme 创建一个学术网站. Easily create a beautiful academic résumé or educational website using Hugo, GitHub, and Netlify.

ODElearning_INN

[ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks

dmm

Deep Markov Models

filterpy

Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.

Graph-Representation-Learning-Tutorial

Code for Data61's tutorial on Graph Representation Learning

Kalman-and-Bayesian-Filters-in-Python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

Sparse-Gaussian-Processes-Revisited

Code for Bayesian Sparse GPs

PyDA

PyDA: A hands-on introduction to dynamical data assimilation with Python

BayesTrack

Bayesian Approaches to State Estimation and Tracking in Multi-Scale Systems

GPflow

Gaussian processes in TensorFlow

VGCN

Variational Graph Convolutional Networks

Sparse-GP

gp-dre

Gaussian Process Density Ratio Estimation

GGP

Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'

BGCN

A Tensorflow implementation of "Bayesian Graph Convolutional Neural Networks" (AAAI 2019).

sequential_design_for_predator_prey_experiments

This repository contains both R and MATLAB code that conducts optimal sequential experimental design for predator-prey experiments. See README.md for more information.

ebonilla.github.io.old

Edwin V. Bonilla's Personal Web Page

STVB

An implementation of the model described in "Structured Variational Inference in Continuous Cox Process Models".

AutoGP

Code for AutoGP

gaussianprocesses

Modern Gaussian Processes: Scalable Inference and Novel Applications

MCPM

Code for MCPM

technicalNotes

Technical notes for stuff