graphistician | Python Ecosystem Directory

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Generalized linear models for neural spike train modeling, in Python! With GPU-accelerated fully-...

Machine learning, in numpy

Bayesian Inverse Graphics for Few-Shot Concept Learning

Random feature latent variable models in Python

Recurrent Switching Linear Dynamical Systems

Talk for SciPy2015 "Deep Learning: Tips From The Road"

Bayesian inference in HSMMs and HMMs

Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on Paddle...

Interpretable neural spike train models with fully-Bayesian inference algorithms

Representation learning on large graphs using stochastic graph convolutions.

Platform for designing and evaluating Graph Neural Networks (GNN)

GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models

Python framework for inference in Hawkes processes.

UNKNOWN

Basic utilities for Bayesian inference