Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
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Updated
Jul 1, 2019 - TeX
Master Thesis on Bayesian Convolutional Neural Network using Variational Inference
📖 R 语言数据分析实战(写作中) Data Analysis in Action Using R
Repo for a book on Bayesian capture-recapture w/ HMMs
Material for course ADA511 at HVL
A list (quite disorganized for now) of papers tackling the Bayesian estimation of Ito processes (and their discrete time version)
The Trendiness of Trends
My MSc thesis: Molecular movies and geometry reconstruction using Coulomb explosion imaging. EDIT: Perfect 2^8 = 256 commits means I should never commit to this repo again.
spectral timing for irregularly sampled data
Estimation of causal effects with small data in the presence of trapdoor variables
Constraining the stellar evolution history of TRAPPIST-1 using MCMC and machine learning with approxposterior
PhD Thesis
MCMC Algorithms for Bayesian inference in the context of Big Data
Course notes for "Bayesian modelling" (MATH80601A)
Interaction-Partitioned Topic Models (IPTM) using a Point Process Approach
notes on machine learning & pattern recognition
This report describes a model for understanding and forecasting loan deferment rates due to labor market shocks using a Bayesian mixed-models approach.
A review of Silverman (2020) "Multiple-systems analysis for the quantification of modern slavery: classical and Bayesian approaches"
A quick start guide to SMC for static Bayesian modelling
This is the final project for the course CS-E5710 Bayesian Data Analysis at Aalto University.
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