A Toolkit for Distributional Control of Generative Models

[AAAI20] TensorFlow implementation of the Collaborative Sampling in Generative Adversarial Networks

pMoSS (p-value Model using the Sample Size) is a Python code to model the p-value as an n-dependent function using Monte Carlo cross-validation. Exploits the dependence on the sample size to characterize the differences among groups of large datasets

Codebase for "Greedy Shapley Client Selection for Communication-Efficient Federated Learning"

Accompanying source code to my Bachelor's thesis at TUHH

Bayesian Non-Parametric Image Segmentation using HDP-MRF

A basic PyTorch implementation of the Collaborative Sampling in Generative Adversarial Networks

This algorithm calculates the zero-point energy of a molecular system by monte-carlo sampling the system's potential energy surface.

My works for EE 511 - Simulation Methods For Stochastic Systems - Spring 2018 - Graduate Coursework at USC - Dr. Osonde A. Osoba

This program computes the particle pair HBT correlation from Monte-Carlo samples of emitted particles

Research Paper about adversarial search

Descriptor and Generator components of CoopNet

Sampling and resampling techniques for random sample generation, estimation, and simulation

Variational autoencoders using Kera's modular design