David's repositories
awesome-ml-for-cybersecurity
:octocat: Machine Learning for Cyber Security
AdvBayesLearnCourse
Course material for the PhD course in Advanced Bayesian Learning
arbitragerepair
Python modules and jupyter notebook examples for the paper Detect and Repair Arbitrage in Price Data of Traded Options.
cvx_short_course
Materials for a short course on convex optimization.
davidrmh.github.io
Repo for github page
deeprob-kit
A Python Library for Deep Probabilistic Modeling
FinRL-Library
A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance, NeurIPS 2020 DRL workshop.
geometric_ml
This repository contains code for applying Riemannian geometry in machine learning.
LTCC-Advanced-Computational-Methods-in-Statistics
Advanced LTCC course in StatisticsThis course will provide an overview of Monte Carlo methods when used for problems in Statistics. After an introduction to simulation, its purpose and challenges, we will cover in more detail Importance Sampling, Markov Chain Monte Carlo and Sequential Monte Carlo. Whilst the main focus will be on the methodology and its relevance to applications, we will often mention relevant theoretical results and their importance for problems in practice.
PGPortfolio
PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).
probai-2021
Materials of the Nordic Probabilistic AI School 2021.
probai-2021-pyro
Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)
TF-Advanced-Techniques
Tensorflow Advanced Technique Specialization
wdro_local_perturbation
Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)