Approximate Bayesian Computation
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Updated
Apr 10, 2017 - Jupyter Notebook
Approximate Bayesian Computation
David Mackay's book review and problem solvings and own python codes, mathematica files
In summer 2017, I was an intern at the Purdue University working under Prof Bruno Ribeiro on improving the training of Restricted Boltzmann Machines. We used the Las Vegas transformation of Markov Chain Monte Carlo method to obtain better samples to estimate the negative phase of the gradient. The model trained via this method achieved a signifi…
Supporting information for Aggregate Size Dependence of Amyloid Adsorption onto Charged Interfaces
Variational autoencoders using Kera's modular design
Accompanying source code to my Bachelor's thesis at TUHH
Descriptor and Generator components of CoopNet
Real-time brain states tracking system and corticothalamic neural field parameter estimation
My works for EE 511 - Simulation Methods For Stochastic Systems - Spring 2018 - Graduate Coursework at USC - Dr. Osonde A. Osoba
Bayesian Non-Parametric Image Segmentation using HDP-MRF
Virtual population generation, fitting, and benchmarking.
Estimating value of PI using Monte-Carlo algorithm
Codes for statistical test of probabilistic seismic hazard assessments.
Finding Areas Using the Monte Carlo Method
Third year mathematics dissertation on variational, laplace and mcmc approximations of bayesian logistic regression
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