Lists (9)
Stars
Resources about time series forecasting and deep learning.
A JAX-based gaussian process structure learning package for time series modelling.
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Introductory workshop on PINNs using the harmonic oscillator
Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflo…
A friendly package for Kepler & TESS time series analysis in Python.
There can be more than Notion and Miro. AFFiNE(pronounced [ə‘fain]) is a next-gen knowledge base that brings planning, sorting and creating all together. Privacy first, open-source, customizable an…
Next-gen fast plotting library running on WGPU using the pygfx rendering engine
Examples of PyMC models, including a library of Jupyter notebooks.
PyTorch implementation of "Drift doesn't Matter: Dynamic Decomposition with Dffusion Reconstruction for Unstable Multivariate Time Series Anomaly Detection" (NeurIPS 2023)
CLU lets you write beautiful training loops in JAX.
Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python ⚡
A curated list of awesome Jupyter widget packages and projects
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
Gravitational-wave data analysis tools in Jax
Custom Bindings for Enzyme Automatic Differentiation Tool and Interfacing with JAX.
Efficient library for spectral analysis in high-energy astrophysics.
Generation of diagrams like flowcharts or sequence diagrams from text in a similar manner as markdown
The lazier way to manage everything docker
A small library of paramaterizations and parameter constraints for PyTrees.
Exploring and eliciting probability distributions
Working through Structure and Interpretation of Classical Mechanics.
JupyterLab computational environment.
Gaussian Process time series analysis with focus on period detection on irregularly-sampled stochastically-varying astronomical time series