davidrmh

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.

BQonRDM

Repository for the paper "Bayesian Quadrature on Riemannian Data Manifolds"

CP-Flow

Convex potential flows

Credal-Portfolios-ICAIF23

cspn

An experimentation project on Sum-Product networks

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

Distributionally-Robust-Optimization-for-Deep-Kernel-Multiple-Instance-Learning

distributionally_robust_optimization

doro

Distributional and Outlier Robust Optimization (ICML 2021)

DupireNN

Neural network local volatility with dupire formula

EinsumNetworks

fast-dro

PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets

FinRL-Library

A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance, NeurIPS 2020 DRL workshop.

gait

Code for the paper GAIT: A Geometric Approach to Information Theory

geometric_ml

This repository contains code for applying Riemannian geometry in machine learning.

kdro

Code for the paper: Kernel Distributionally Robust Optimization

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.

mvae

Mixed-curvature Variational Autoencoders (ICLR 2020)

P-DRO

Code for the paper "Modeling the Second Player in Distributionally Robust Optimization"

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/)

RAT-SPN

Code for UAI'19: Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning

TF-Advanced-Techniques

Tensorflow Advanced Technique Specialization

wdro_local_perturbation

Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)

week4DavidMontalvan

Package For Week 4