Linking pages
- Google Research: Looking Back at 2019, and Forward to 2020 and Beyond – Google AI Blog https://ai.googleblog.com/2020/01/google-research-looking-back-at-2019.html 18 comments
- GitHub - r0f1/datascience: Curated list of Python resources for data science. https://github.com/r0f1/datascience 0 comments
- Why is numerical analysis still a big issue? https://yablak.substack.com/p/why-is-numerical-analysis-still-a 0 comments
- MCMC for big datasets -- faster sampling with JAX and the GPU – Martin Ingram's Blog – Stats, Coding, and Tennis https://martiningram.github.io/mcmc-comparison/ 0 comments
- GitHub - google/lightweight_mmm: LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information. https://github.com/google/lightweight_mmm 0 comments
- GitHub - normal-computing/posteriors: Uncertainty quantification with PyTorch https://github.com/normal-computing/posteriors 0 comments
Linked pages
- GitHub - google/jax: Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more https://github.com/google/jax 99 comments
- Stan User’s Guide https://mc-stan.org/docs/2_18/stan-users-guide/reparameterization-section.html 3 comments
- Statistical Rethinking | Richard McElreath http://xcelab.net/rm/statistical-rethinking/ 1 comment
- GPU in Windows Subsystem for Linux (WSL) | NVIDIA Developer https://developer.nvidia.com/cuda/wsl 0 comments
- jax/cloud_tpu_colabs at main · google/jax · GitHub https://github.com/google/jax/tree/master/cloud_tpu_colabs 0 comments