Stars
Astronomy Broker based on Apache Spark
Lightweight, useful implementation of conformal prediction on real data.
📖 A curated list of resources dedicated to Natural Language Processing (NLP)
A curated list of NLP resources focused on Transformer networks, attention mechanism, GPT, BERT, ChatGPT, LLMs, and transfer learning.
What can I do with a LLM model?
A comprehensive list of papers using large language/multi-modal models for Robotics/RL, including papers, codes, and related websites
Python implementation of the R stargazer multiple regression model creation tool
A package to describe amortized (conditional) normalizing-flow PDFs defined jointly on tensor products of manifolds with coverage control. The connection between different manifolds is fixed via an…
500+ Data Structures and Algorithms practice problems
Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
Python Library for Causal and Probabilistic Modeling using Bayesian Networks
Replication code and downloadable example data sets for The Effect
Homework assignments to go along with The Effect
📖 An approachable introduction to Assembly.
Official release of code for "Oops I Took A Gradient: Scalable Sampling for Discrete Distributions"
Important concepts in numerical linear algebra and related areas
📚 Collaborative cheatsheets for console commands
A list of Medical imaging datasets.
Computations and statistics on manifolds with geometric structures.
"Deep Generative Modeling": Introductory Examples
Awesome resources on normalizing flows.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a community of users and contributors by focusing initially o…
Fast, flexible and easy to use probabilistic modelling in Python.
Best Practices for Using eBird Data
A small package to create visualizations of PyTorch execution graphs