ludwigwinkler

BayesianOptimization

Bayesian Optimization with Gaussian Processes

EhrenfestDiffusion

Transfer Learning between Discrete and Continuous Diffusion Model

hamiltorch

PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC)

JaxLightning

Running Jax in PyTorch Lightning

ludwigwinkler.github.io

Ludwig Winklers Github.io

MCMC-with-Uncertain-Energies

MLMD

pytorch_MCMC

Lightweight MCMC sampling for PyTorch Models aka My Corona Project

pytorch_ProbabilisticLayers

Bayesian Neural Networks with Parallelized Sampling of LogLikelihood

ludwigwinkler/JaxLightning

Running Jax in PyTorch Lightning

ludwigwinkler/pytorch_MCMC

Lightweight MCMC sampling for PyTorch Models aka My Corona Project

ludwigwinkler/pytorch_ProbabilisticLayers

Bayesian Neural Networks with Parallelized Sampling of LogLikelihood

ludwigwinkler/EhrenfestDiffusion

Transfer Learning between Discrete and Continuous Diffusion Model

ludwigwinkler/BayesianOptimization

Bayesian Optimization with Gaussian Processes

ludwigwinkler/hamiltorch

PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC)

ludwigwinkler/ludwigwinkler.github.io

Ludwig Winklers Github.io

ludwigwinkler/MCMC-with-Uncertain-Energies

ludwigwinkler/MLMD

ludwigwinkler/18337

18.337 - Parallel Computing and Scientific Machine Learning

ludwigwinkler/18S191

Course 18.S191 at MIT, fall 2020 - Introduction to computational thinking with Julia:

ludwigwinkler/csgmcmc

Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning

ludwigwinkler/DiffSim

ludwigwinkler/diffusion_schrodinger_bridge

PyTorch Implementation of DSB for Score Based Generative Modeling. Experiments managed using Hydra.

ludwigwinkler/IBExperiments

Reinforcement Learning in Highly Stochastic Environment with the Industrial Benchmark Environment

ludwigwinkler/improved-diffusion

Release for Improved Denoising Diffusion Probabilistic Models

ludwigwinkler/MLTalks

Machine Learning Talks (Difficulty of Training RNNs, Uncertain MCMC Sampling)

ludwigwinkler/ncsn

Noise Conditional Score Networks (NeurIPS 2019, Oral)

ludwigwinkler/offshoreleaks-data-packages

Tools to produce and share the downloadable Neo4j packages and guides

ludwigwinkler/pytorch-fid

Compute FID scores with PyTorch.

ludwigwinkler/pytorch-mcmc

Little Markov Chain Monte Carlo library built on PyTorch

ludwigwinkler/riemannian-score-sde

Score-based generative models for compact manifolds

ludwigwinkler/score_sde_pytorch

PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

ludwigwinkler/simple-diffusion-model

Pedagogical codebase for a simplified score-based generative model design, with training loop

ludwigwinkler/SimpleParsing

Simple, Elegant, Typed Argument Parsing with argparse

ludwigwinkler/SinkhornAutoDiff

Toolbox to integrate optimal transport loss functions using automatic differentiation and Sinkhorn's algorithm

ludwigwinkler/sliced_score_matching

Code for reproducing results in the sliced score matching paper (UAI 2019)

ludwigwinkler/tauLDR

Code for the paper https://arxiv.org/abs/2205.14987v2

ludwigwinkler/torch-fidelity

High-fidelity performance metrics for generative models in PyTorch

ludwigwinkler/wassdistance

Approximating Wasserstein distances with PyTorch