Stars
The official GitHub page for the survey paper "A Survey of Large Language Models".
A general-purpose, deep learning-first library for constrained optimization in PyTorch
Gradient Estimation with Discrete Stein Operators (NeurIPS 2022)
A collection of resources and papers on Diffusion Models
A curated list of awesome papers on dataset distillation and related applications.
Accompanies and reproduces results from the paper "Control Variates for Slate Off-Policy Evaluation"
Code for the paper: "Tensor Programs II: Neural Tangent Kernel for Any Architecture"
Pytorch domain library for recommendation systems
[ICLR'22] [KDD'22] [IJCAI'24] Implementation of "Graph Condensation for Graph Neural Networks"
Open-source code for paper "Dataset Distillation"
Modularized Implementation of Deep RL Algorithms in PyTorch
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Reduce end to end training time from days to hours (or hours to minutes), and energy requirements/costs by an order of magnitude using coresets and data selection.
Awesome coreset/core-set/subset/sample selection works.
Oh my tmux! My self-contained, pretty & versatile tmux configuration made with 💛🩷💙🖤❤️🤍
An offline deep reinforcement learning library
Policy Gradient is all you need! A step-by-step tutorial for well-known PG methods.
OPE Tools based on Empirical Study of Off Policy Policy Estimation paper.
Learning Fair Representations for Recommendation: A Graph-based Perspective, WWW2021
ECLARE: Extreme Classification with Label Graph Correlations
DECAF: Deep Extreme Classification with Label Features
An index of algorithms for offline reinforcement learning (offline-rl)
Gathers machine learning and deep learning models for Stock forecasting including trading bots and simulations
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Advers…
A curated list of community detection research papers with implementations.