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Name: Ludwig Winkler
Type: User
Bio: PhD Student at TU Berlin Machine Learning Group
Location: Berlin
Name: Ludwig Winkler
Type: User
Bio: PhD Student at TU Berlin Machine Learning Group
Location: Berlin
18.337 - Parallel Computing and Scientific Machine Learning
Course 18.S191 at MIT, fall 2020 - Introduction to computational thinking with Julia:
Bayesian Optimization with Gaussian Processes
Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
PyTorch Implementation of DSB for Score Based Generative Modeling. Experiments managed using Hydra.
Transfer Learning between Discrete and Continuous Diffusion Model
PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC)
Reinforcement Learning in Highly Stochastic Environment with the Industrial Benchmark Environment
Release for Improved Denoising Diffusion Probabilistic Models
Running Jax in PyTorch Lightning
Ludwig Winklers Github.io
Machine Learning Talks (Difficulty of Training RNNs, Uncertain MCMC Sampling)
Noise Conditional Score Networks (NeurIPS 2019, Oral)
Tools to produce and share the downloadable Neo4j packages and guides
Compute FID scores with PyTorch.
Little Markov Chain Monte Carlo library built on PyTorch
Lightweight MCMC sampling for PyTorch Models aka My Corona Project
Bayesian Neural Networks with Parallelized Sampling of LogLikelihood
Score-based generative models for compact manifolds
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
Pedagogical codebase for a simplified score-based generative model design, with training loop
Simple, Elegant, Typed Argument Parsing with argparse
Toolbox to integrate optimal transport loss functions using automatic differentiation and Sinkhorn's algorithm
Code for reproducing results in the sliced score matching paper (UAI 2019)
Code for the paper https://arxiv.org/abs/2205.14987v2
High-fidelity performance metrics for generative models in PyTorch
Approximating Wasserstein distances with PyTorch
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.