Pinned Repositories
BayesianOptimization
Bayesian Optimization with Gaussian Processes
EhrenfestDiffusion
Transfer Learning between Discrete and Continuous Diffusion Model
genai
some notes
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's Repositories
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/genai
some notes
ludwigwinkler/hamiltorch
PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC)
ludwigwinkler/ludwigwinkler.github.io
Ludwig Winklers Github.io
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/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-lightning
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
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