Pinned Repositories
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.
article_msc_degree
Article from my master thesis in computer science
awesome-ml-for-cybersecurity
:octocat: Machine Learning for Cyber Security
bayesian-machine-learning
Notebooks about Bayesian methods for machine learning
BQonRDM
Repository for the paper "Bayesian Quadrature on Riemannian Data Manifolds"
CIC-A18
Semester A18 MSc. Computer Science
CIC-B18
Clusters_Shinny
Computational_Finance
davidrmh's Repositories
davidrmh/awesome-ml-for-cybersecurity
:octocat: Machine Learning for Cyber Security
davidrmh/AdvBayesLearnCourse
Course material for the PhD course in Advanced Bayesian Learning
davidrmh/arbitragerepair
Python modules and jupyter notebook examples for the paper Detect and Repair Arbitrage in Price Data of Traded Options.
davidrmh/BQonRDM
Repository for the paper "Bayesian Quadrature on Riemannian Data Manifolds"
davidrmh/CP-Flow
Convex potential flows
davidrmh/Credal-Portfolios-ICAIF23
davidrmh/cspn
An experimentation project on Sum-Product networks
davidrmh/cvx_short_course
Materials for a short course on convex optimization.
davidrmh/davidrmh.github.io
Repo for github page
davidrmh/deeprob-kit
A Python Library for Deep Probabilistic Modeling
davidrmh/Distributionally-Robust-Optimization-for-Deep-Kernel-Multiple-Instance-Learning
davidrmh/distributionally_robust_optimization
davidrmh/doro
Distributional and Outlier Robust Optimization (ICML 2021)
davidrmh/DupireNN
Neural network local volatility with dupire formula
davidrmh/EinsumNetworks
davidrmh/Evidential-Time-Series-Clustering
davidrmh/fast-dro
PyTorch implementation of efficient algorithms for DRO with CVaR and Chi-Square uncertainty sets
davidrmh/FinRL-Library
A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance, NeurIPS 2020 DRL workshop.
davidrmh/gait
Code for the paper GAIT: A Geometric Approach to Information Theory
davidrmh/geometric_ml
This repository contains code for applying Riemannian geometry in machine learning.
davidrmh/kdro
Code for the paper: Kernel Distributionally Robust Optimization
davidrmh/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.
davidrmh/mvae
Mixed-curvature Variational Autoencoders (ICLR 2020)
davidrmh/P-DRO
Code for the paper "Modeling the Second Player in Distributionally Robust Optimization"
davidrmh/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).
davidrmh/probai-2021
Materials of the Nordic Probabilistic AI School 2021.
davidrmh/probai-2021-pyro
Repo for the Tutorials of Day1-Day3 of the Nordic Probabilistic AI School 2021 (https://probabilistic.ai/)
davidrmh/TF-Advanced-Techniques
Tensorflow Advanced Technique Specialization
davidrmh/wdro_local_perturbation
Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)
davidrmh/xai-trading-via-image