Reverse Dependencies of sphinxcontrib-katex

The following projects have a declared dependency on sphinxcontrib-katex:

• analogvnn — A fully modular framework for modeling and optimizing analog/photonic neural networks
• angst — Angular statistics
• bayesian-models — A package for building common bayesian models in pymc
• captum — Model interpretability for PyTorch
• composer — Composer is a PyTorch library that enables you to train neural networks faster, at lower cost, and to higher accuracy.
• continual-inference — A Python library for Continual Inference Networks in PyTorch
• cr-sparse — Accelerated sparse representations and compressive sensing
• cr-wavelets — Wavelets with JAX
• crikit — Constitutive Relation Inference Toolkit
• d2py — Dive into Python.
• deduplicationdict — A dictionary that de-duplicates values.
• deel-datasets — Dataset loader for DEEL datasets
• deel-torchlip — PyTorch implementation for k-Lipschitz layers
• deeptime — Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation.
• dmme — Diffusion Models Made Easy
• finesse — Simulation tool for modelling laser interferometers
• Gammalearn — A framework to easily train deep learning model on Imaging Atmospheric Cherenkov Telescopes data
• glass — Generator for Large Scale Structure
• histolab — Python library for Digital Pathology Image Processing
• maze-world — Random maze environments with different size and complexity for reinforcement learning and planning research. This is in-particular to investigate generalization and planning ability in dynamically changing environment.
• mofdscribe — Ecosystem for digital reticular chemistry
• moleculetda — Toolkit for using topological data analysis representations.
• mosaicml — Composer is a PyTorch library that enables you to train neural networks faster, at lower cost, and to higher accuracy.
• mosaicml-cli — Interact with the Databricks Mosaic AI training platform from python or a command line interface
• mosaicml-streaming — Streaming lets users create PyTorch compatible datasets that can be streamed from cloud-based object stores
• naturf — The Neighborhood Adaptive Tissues for Urban Resilience Futures tool (NATURF) is a Python workflow that generates data readable by the Weather Research and Forecasting (WRF) model. The NATURF Python modules use shapefiles containing building footprint and height data as input to calculate 132 building parameters at any resolution and converts the parameters into a binary file format.
• neuralcompression — A collection of tools for neural compression enthusiasts
• optax — A gradient processing and optimisation library in JAX.
• penzai — Penzai: A JAX research toolkit for building, editing, and visualizing neural networks.
• protoflow — Highly extensible, GPU-supported Learning Vector Quantization (LVQ) toolbox built using Tensorflow 2.x and its Keras API.
• prototorch — Highly extensible, GPU-supported Learning Vector Quantization (LVQ) toolbox built using PyTorch and its nn API.
• prototorch-models — Pre-packaged prototype-based machine learning models using ProtoTorch and PyTorch-Lightning.
• pyagree — A simple Python package to compute some inter-rater agreement measures.
• pyberny — Molecular/crystal structure optimizer
• pymanopt — Toolbox for optimization on Riemannian manifolds with support for automatic differentiation
• pypose — To connect classic robotics with modern learning methods.
• pytorch-stream — Building blocks for Continual Inference Networks in PyTorch
• sphinx_seeta_theme — Sphinx theme for seeta documentations.
• torch-stream — Building blocks for Continual Inference Networks in PyTorch
• xyzstyle — Sphinx demo.
• yahp — Yet Another HyperParameter framework
• zfista — A globally convergent fast iterative shrinkage-thresholding algorithm with a new momentum factor for single and multi-objective convex optimization