Beast code in Giters

Ekaterina Khramtsova's starred repositories

Dassl.pytorch

A PyTorch toolbox for domain generalization, domain adaptation and semi-supervised learning.

Language:PythonMIT113800

DomainBed

DomainBed is a suite to test domain generalization algorithms

Language:PythonMIT135400

test-time-adaptation

A repository and benchmark for online test-time adaptation.

Language:PythonMIT16200

augnet

Code of "Deep invariant networks with differentiable augmentation layers"

Language:PythonBSD-2-Clause1800

tent

ICLR21 Tent: Fully Test-Time Adaptation by Entropy Minimization

Language:PythonMIT33700

tevatron

Tevatron - A flexible toolkit for neural retrieval research and development.

Language:PythonApache-2.044300

RandConv

Code for ICLR2021 paper "Robust and Generalizable Visual Representation Learning via Random Convolutions"

Language:Python6000

filter-pruning-geometric-median

Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration (CVPR 2019 Oral)

Language:Python58000

awesome-ehr-deeplearning

Curated list of awesome papers for electronic health records(EHR) mining, machine learning, and deep learning.

CC0-1.040500

topological-autoencoders

Code for the paper "Topological Autoencoders" by Michael Moor, Max Horn, Bastian Rieck, and Karsten Borgwardt.

Language:PythonBSD-3-Clause13500

hybridnet

Code for "HybridNet: Classification and Reconstruction Cooperation for Semi-Supervised Learning"

Language:PythonNOASSERTION500

mean-teacher

A state-of-the-art semi-supervised method for image recognition

Language:PythonNOASSERTION156600

jmlr_2019

Code for JMLR paper ``Learning Representations of Persistence Barcodes``

Language:Jupyter Notebook2200

CLAM

Data-efficient and weakly supervised computational pathology on whole slide images - Nature Biomedical Engineering

Language:PythonGPL-3.098700

PySyft

Perform data science on data that remains in someone else's server

Language:Jupyter NotebookApache-2.0938200

federated-learning

A PyTorch Implementation of Federated Learning http://doi.org/10.5281/zenodo.4321561

Language:PythonMIT121900