-
Google
- Zurich, Switzerland
- https://www.linkedin.com/in/willi-gierke-5221a7b5
Stars
Companion webpage to the book "Mathematics For Machine Learning"
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Master programming by recreating your favorite technologies from scratch.
Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"
IMO Grand Challenge for Artificial Intelligence
Latex code for making neural networks diagrams
by ex-googlers, for ex-googlers - a lookup table of similar tech & services
Book in preparation: introduction to theoretical computer science
All Algorithms implemented in Python
This cheasheet is aimed at the CTF Players and Beginners to help them understand the fundamentals of Privilege Escalation with examples.
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…
Best practice and tips & tricks to write scientific papers in LaTeX, with figures generated in Python or Matlab.
Learning Latent Dynamics for Planning from Pixels
disentanglement_lib is an open-source library for research on learning disentangled representations.
A comprehensive 10-page probability cheatsheet that covers a semester's worth of introduction to probability.
Low-code framework for building custom LLMs, neural networks, and other AI models
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
Everything you need to know to get the job.
Assessing Generative Models via Precision and Recall (official repository)
A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.