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Collection of awesome test-time (domain/batch/instance) adaptation methods
Implementation of SCAFFOLD: Stochastic Controlled Averaging for Federated Learning
PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020).
Code for "Federated Accelerated Stochastic Gradient Descent" (NeurIPS 2020)
Distributionally robust neural networks for group shifts
Single Cell multimodal data scripts for downloading datasets
OpenDataVal: a Unified Benchmark for Data Valuation in Python (NeurIPS 2023)
Lightweight Python library for in-memory matrix completion.
A simulator for single-cell expression data guided by gene regulatory networks
Google Research
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations.
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning …
FedScale is a scalable and extensible open-source federated learning (FL) platform.
Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"
DAGs with NO TEARS: Continuous Optimization for Structure Learning
Implementation of EF and EF21 methods and their comparison on several tasks
Functional Graphical Models via Neighborhood Selection Approach
Python implementation of elastic-net regularized generalized linear models
Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs o…
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media