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adversarial_active_learning

Adversarial Active Learning for Deep Networks

bert-chinese-ner

使用预训练语言模型BERT做中文NER

bert-ner

This is a named entity recognizer based on pytorch-pretrained-bert.

beto

BETO - Spanish version of the BERT model

deep-learning-pytorch-huggingface

densenet-pytorch

Implementation of DenseNets Using PyTorch

diracnets

Training Very Deep Neural Networks Without Skip-Connections

ece885_mini2

federated-learning-pytorch

Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data

gntm

google-research

Google AI Research

large_margin_loss_pytorch

A PyTorch Implementation of a Large Margin Deep Networks for Classification

leaf

Leaf: A Benchmark for Federated Settings

leetcode

libtlda

Library of transfer learners and domain-adaptive classifiers.

ls-llama

Official Code For Label Supervised LLaMA Finetuning

mixed-effect-composite-rnn-gaussian-process

Personalized and Reliable Predictive Models for Healthcare (의료 데이터 기반 신뢰 가능한 개인화된 예측(진단) 모델)

mlr

Metric Learning to Rank

ner-bert-crf

ner-pytorch

LSTM+CRF NER

pate_torch

Implementation of PATE technique described in https://arxiv.org/pdf/1610.05755.pdf

pytorch-bilstm-crf

PyTorch implementation of CRF using BiLSTM (with word and char level embeddings) for Named Entity Recognition

pytorch-crf

:fire: A PyTorch implementation of a Bi-LSTM CRF with character-level features

pytorch-logistic-regression

Running logistic regression using torch lib in python.

regcgan

representer_point_selection

code release for Representer point Selection for Explaining Deep Neural Network in NeurIPS 2018

statsmodels

Statsmodels: statistical modeling and econometrics in Python

tranad

[VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.