Pinned Repositories
abcpy
ABCpy package
ad
Fast, transparent calculations of first and second-order automatic differentiation
adawhatever
MATLAB implementation of AdaGrad, Adam, Adamax, Adadelta etc.
arxivsearch
Pulls papers from arXiv on a weekly basis
autograd
Efficiently computes derivatives of numpy code.
autolrs
Automatic learning-rate scheduler
awesome-normalizing-flows
A list of awesome resources on normalizing flows.
BADAM
Code which implements BADAM
Bambi_resources
Educational resources
bayes-nn
Lecture notes on Bayesian deep learning
monicaio's Repositories
monicaio/mc_gradients
monicaio/BNAF
Pytorch implementation of Block Neural Autoregressive Flow
monicaio/awesome-normalizing-flows
A list of awesome resources on normalizing flows.
monicaio/papers
Edward content including papers, posters, and talks
monicaio/QMCSoftware
monicaio/adawhatever
MATLAB implementation of AdaGrad, Adam, Adamax, Adadelta etc.
monicaio/normalizing_flows
Pytorch implementations of density estimation algorithms: BNAF, Glow, MAF, RealNVP, planar flows
monicaio/pytorch_flows
Implementation and tutorials of normalizing flows with the novel distributions module
monicaio/img2latex-mathpix
An image to LaTeX tool by MathpixOCR API and JavaFX
monicaio/BADAM
Code which implements BADAM
monicaio/nsf
Code for Neural Spline Flows paper
monicaio/gradient_descent_viz
interactive visualization of 5 popular gradient descent methods with step-by-step illustration and hyperparameter tuning UI
monicaio/dataset-downloader
monicaio/bayesian-basics
:no_entry_sign: :leftwards_arrow_with_hook: A document that introduces Bayesian data analysis.
monicaio/Bayesian-Neural-Networks
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
monicaio/deeplearning-with-tensorflow-notes
龙曲良《TensorFlow深度学习》学习笔记及代码，采用TensorFlow2.0.0版本
monicaio/probabilistic-models
Collection of probabilistic models and inference algorithms
monicaio/bayes-workflow-book
Source files for the book "Bayesian Workflow Using Stan"
monicaio/sampling-methods-numpy
This repository contains implementations of some basic sampling methods in numpy.
monicaio/noisy-K-FAC
Natural Gradient, Variational Inference
monicaio/zhusuan
A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow
monicaio/dl-with-bayes
Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"
monicaio/edward
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
monicaio/Python-Project
我的简单python 程序
monicaio/machine_learning_derivation
notes of machine learning algorithm derivation
monicaio/maf
Masked Autoregressive Flow
monicaio/variational-smc
Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
monicaio/LIBS2ML
LIBS2ML: A Library for Scalable Second Order Machine Learning Algorithms
monicaio/Stein-Variational-Gradient-Descent
code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
monicaio/PCA_MUSIC
Matlab code for my paper "Bayesian inference for PCA and MUSIC algorithms with unknown number of sources", IEEE Trans. on signal processing, 2018