The implementation of the algorithm in the paper "Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data" published in ICML 2020.

Related tags

Deep LearningDS3L
Overview

DS3L

This is the code for paper "Safe Deep Semi-Supervised Learning for Unseen-Class Unlabeled Data" published in ICML 2020.

Setups

The code is implemented with Python and Pytorch.

Running D3SL for benchmark datasets

Here is an example:

python train.py --dataset MNIST --ratio 0.6 --n_labels 60 --iterations 200000

Acknowledgements

We thank the Pytorch implementation on Meta-Net (https://github.com/xjtushujun/meta-weight-ne) and learning-to-reweight-examples(https://github.com/danieltan07/learning-to-reweight-examples).

Contact

If you have any questions, please contact Lan-Zhe Guo ([email protected]).

Owner
Guolz
I am a M.Sc. student in LAMDA Group, Nanjing University. I am interested in machine learning and deep learning. My website: www.guolz.com
Guolz
Rapid experimentation and scaling of deep learning models on molecular and crystal graphs.

LitMatter A template for rapid experimentation and scaling deep learning models on molecular and crystal graphs. How to use Clone this repository and

Nathan Frey 32 Dec 06, 2022
[CVPR 2022 Oral] Versatile Multi-Modal Pre-Training for Human-Centric Perception

Versatile Multi-Modal Pre-Training for Human-Centric Perception Fangzhou Hong1  Liang Pan1  Zhongang Cai1,2,3  Ziwei Liu1* 1S-Lab, Nanyang Technologic

Fangzhou Hong 96 Jan 03, 2023
A Benchmark For Measuring Systematic Generalization of Multi-Hierarchical Reasoning

Orchard Dataset This repository contains the code used for generating the Orchard Dataset, as seen in the Multi-Hierarchical Reasoning in Sequences: S

Bill Pung 1 Jun 05, 2022
MapReader: A computer vision pipeline for the semantic exploration of maps at scale

MapReader A computer vision pipeline for the semantic exploration of maps at scale MapReader is an end-to-end computer vision (CV) pipeline designed b

Living with Machines 25 Dec 26, 2022
Official PyTorch implementation of GDWCT (CVPR 2019, oral)

This repository provides the official code of GDWCT, and it is written in PyTorch. Paper Image-to-Image Translation via Group-wise Deep Whitening-and-

WonwoongCho 135 Dec 02, 2022
Pytorch Implementation of Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic

Pytorch Implementation of Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic [Paper] [Colab is coming soon] Approach Example Usage To r

170 Jan 03, 2023
On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification

Understanding Bayesian Classification This repository hosts the code to reproduce the results presented in the paper On Uncertainty, Tempering, and Da

Sanyam Kapoor 18 Nov 17, 2022
Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集

English | 简体中文 Latest News 2021.10.25 Paper "Docking-based Virtual Screening with Multi-Task Learning" is accepted by BIBM 2021. 2021.07.29 PaddleHeli

633 Jan 04, 2023
Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank

This repository provides the official code for replicating experiments from the paper: Semi-Supervised Semantic Segmentation with Pixel-Level Contrast

Iñigo Alonso Ruiz 58 Dec 15, 2022
use tensorflow 2.0 to tell a dog and cat from a specified picture

dog_or_cat use tensorflow 2.0 to tell a dog and cat from a specified picture This is one of the classic experiments for the introduction of deep learn

你这个代码我看不懂 1 Oct 22, 2021
A pre-trained model with multi-exit transformer architecture.

ElasticBERT This repository contains finetuning code and checkpoints for ElasticBERT. Towards Efficient NLP: A Standard Evaluation and A Strong Baseli

fastNLP 48 Dec 14, 2022
Automatic differentiation with weighted finite-state transducers.

GTN: Automatic Differentiation with WFSTs Quickstart | Installation | Documentation What is GTN? GTN is a framework for automatic differentiation with

100 Dec 29, 2022
Orange Chicken: Data-driven Model Generalizability in Crosslinguistic Low-resource Morphological Segmentation

Orange Chicken: Data-driven Model Generalizability in Crosslinguistic Low-resource Morphological Segmentation This repository contains code and data f

Zoey Liu 0 Jan 07, 2022
The fundamental package for scientific computing with Python.

NumPy is the fundamental package needed for scientific computing with Python. Website: https://www.numpy.org Documentation: https://numpy.org/doc Mail

NumPy 22.4k Jan 09, 2023
Algo-burn - Script to configure an Algorand address as a "burn" address for one or more ASA tokens

Algorand Burn Address This is a simple script to illustrate how a "burn address"

GSD 5 May 10, 2022
RoMa: A lightweight library to deal with 3D rotations in PyTorch.

RoMa: A lightweight library to deal with 3D rotations in PyTorch. RoMa (which stands for Rotation Manipulation) provides differentiable mappings betwe

NAVER 90 Dec 27, 2022
AdamW optimizer and cosine learning rate annealing with restarts

AdamW optimizer and cosine learning rate annealing with restarts This repository contains an implementation of AdamW optimization algorithm and cosine

Maksym Pyrozhok 133 Dec 20, 2022
clDice - a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation

README clDice - a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation CVPR 2021 Authors: Suprosanna Shit and Johannes C. Paetzo

110 Dec 29, 2022
FIRA: Fine-Grained Graph-Based Code Change Representation for Automated Commit Message Generation

FIRA is a learning-based commit message generation approach, which first represents code changes via fine-grained graphs and then learns to generate commit messages automatically.

Van 21 Dec 30, 2022
Simple tutorials on Pytorch DDP training

pytorch-distributed-training Distribute Dataparallel (DDP) Training on Pytorch Features Easy to study DDP training You can directly copy this code for

Ren Tianhe 188 Jan 06, 2023