Stars
Datasets derived from US census data
Covid-19 Twitter dataset for non-commercial research use and pre-processing scripts - under active development
Reinforcement Learning with Perturbed Reward, AAAI 2020
Robust Bi-Tempered Logistic Loss Based on Bregman Divergences. https://arxiv.org/pdf/1906.03361.pdf
Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Needs to generate some texts to test if my GUI rendering codes good or not. so I made this.
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…
Interpretability Methods for tf.keras models with Tensorflow 2.x
A collection of infrastructure and tools for research in neural network interpretability.
A curated list of awesome responsible machine learning resources.
The PSL software from the University of Maryland and the University of California Santa Cruz
FairNAS: Rethinking Evaluation Fairness of Weight Sharing Neural Architecture Search
PyTorch original implementation of Cross-lingual Language Model Pretraining.
Examples of using sparse attention, as in "Generating Long Sequences with Sparse Transformers"
Code for the paper "Large-Scale Study of Curiosity-Driven Learning"
Python library that makes it easy for data scientists to create charts.
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
上海交通大学 LaTeX 论文模板 | Shanghai Jiao Tong University LaTeX Thesis Template
Cool vision, learning, and graphics papers on Cats!
The end goal is a simple application for translating text in the terminal. Text can be generated interactively or programmatically in the shell environment.
Open-Source Distributed Reinforcement Learning Framework by Stanford Vision and Learning Lab
An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.