This repo includes our code for evaluating and improving transferability in domain generalization (NeurIPS 2021)

Overview

Transferability for domain generalization

This repo is for evaluating and improving transferability in domain generalization (NeurIPS 2021), based on our paper Quantifying and Improving Transferability in Domain Generalization. The code is adapted from the DomainBed suite.

  • python version: 3.6
  • pytorch version: 1.7.1
  • cuda version: 10.2

We aim to achieve two goals:

  • measure the transferability between domains
  • implement the Transfer algorithm

Currently we support four datasets:

  • RotatedMNIST
  • PACS
  • OfficeHome
  • WILDS-FMoW

To get started, first obtain a datasplit of a dataset. For example, if the dataset is RotatedMNIST, we run:

python save_datasets.py --dataset=RotatedMNIST

The next step is to run the training algorithm. For example, if we want to train ERM:

python -m train --algorithm=ERM --dataset=RotatedMNIST

The repo also supports the training of Transfer algorithm. For instance, if we want to train Transfer on RotatedMNIST with 30 steps per inner loop with projection radius 10.0:

python -m train --algorithm=Transfer --dataset=RotatedMNIST \
--output_dir="results" \
--steps=8000 \
--lr=0.01 \
--lr_d=0.01 \
--d_steps_per_g=30 \
--train_delta=10.0

Finally we could run evaluation after the training process. For example, if we want to evaluate ERM with delta=2.0:

python transfer_measure.py --algorithm=ERM --delta=2.0 --adv_epoch=10 --seed=0

Similarly, if we run:

python -m transfer_measure \
--d_steps_per_g=30 \
--train_delta=10.0 \
--algorithm=Transfer \
--dataset=RotatedMNIST \
--delta=2.0 \
--adv_epoch=10 \
--seed=0

We could evaluate the Transfer algorithm.

License

This source code is released under the MIT license, included here.

Citation

Comments are welcome! Please use the following bib if you use our code in your research:

@article{zhang2021quantifying,
      title={Quantifying and Improving Transferability in Domain Generalization}, 
      author={Guojun Zhang and Han Zhao and Yaoliang Yu and Pascal Poupart},
      year={2021},
      journal={Advances in neural information processing systems},
}
Owner
gordon
CS Ph.D. in machine learning.
gordon
Repository for the paper "From global to local MDI variable importances for random forests and when they are Shapley values"

From global to local MDI variable importances for random forests and when they are Shapley values Antonio Sutera ( Antonio Sutera 3 Feb 23, 2022

Source code for EquiDock: Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking (ICLR 2022)

Source code for EquiDock: Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking (ICLR 2022) Please cite "Independent SE(3)-Equivar

Octavian Ganea 154 Jan 02, 2023
The official repo of the CVPR 2021 paper Group Collaborative Learning for Co-Salient Object Detection .

GCoNet The official repo of the CVPR 2021 paper Group Collaborative Learning for Co-Salient Object Detection . Trained model Download final_gconet.pth

Qi Fan 46 Nov 17, 2022
Official implementation for the paper: "Multi-label Classification with Partial Annotations using Class-aware Selective Loss"

Multi-label Classification with Partial Annotations using Class-aware Selective Loss Paper | Pretrained models Official PyTorch Implementation Emanuel

99 Dec 27, 2022
Python Algorithm Interview Book Review

파이썬 알고리즘 인터뷰 책 리뷰 리뷰 IT 대기업에 들어가고 싶은 목표가 있다. 내가 꿈꿔온 회사에서 일하는 사람들의 모습을 보면 멋있다고 생각이 들고 나의 목표에 대한 열망이 강해지는 것 같다. 미래의 핵심 사업 중 하나인 SW 부분을 이끌고 발전시키는 우리나라의 I

SharkBSJ 1 Dec 14, 2021
Recursive Bayesian Networks

Recursive Bayesian Networks This repository contains the code to reproduce the results from the NeurIPS 2021 paper Lieck R, Rohrmeier M (2021) Recursi

Robert Lieck 11 Oct 18, 2022
Readings for "A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Therapy, and Drug-Drug Interaction Prediction."

Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp

AstraZeneca 79 Jan 05, 2023
Code to accompany our paper "Continual Learning Through Synaptic Intelligence" ICML 2017

Continual Learning Through Synaptic Intelligence This repository contains code to reproduce the key findings of our path integral approach to prevent

Ganguli Lab 82 Nov 03, 2022
DecoupledNet is semantic segmentation system which using heterogeneous annotations

DecoupledNet: Decoupled Deep Neural Network for Semi-supervised Semantic Segmentation Created by Seunghoon Hong, Hyeonwoo Noh and Bohyung Han at POSTE

Hyeonwoo Noh 74 Sep 22, 2021
COD-Rank-Localize-and-Segment (CVPR2021)

COD-Rank-Localize-and-Segment (CVPR2021) Simultaneously Localize, Segment and Rank the Camouflaged Objects Full camouflage fixation training dataset i

JingZhang 52 Dec 20, 2022
Lite-HRNet: A Lightweight High-Resolution Network

LiteHRNet Benchmark 🔥 🔥 Based on MMsegmentation 🔥 🔥 Cityscapes FCN resize concat config mIoU last mAcc last eval last mIoU best mAcc best eval bes

16 Dec 12, 2022
Explaining Hyperparameter Optimization via PDPs

Explaining Hyperparameter Optimization via PDPs This repository gives access to an implementation of the methods presented in the paper submission “Ex

2 Nov 16, 2022
torchbearer: A model fitting library for PyTorch

Note: We're moving to PyTorch Lightning! Read about the move here. From the end of February, torchbearer will no longer be actively maintained. We'll

632 Dec 13, 2022
Yolov5 + Deep Sort with PyTorch

딥소트 수정중 Yolov5 + Deep Sort with PyTorch Introduction This repository contains a two-stage-tracker. The detections generated by YOLOv5, a family of obj

1 Nov 26, 2021
ELSED: Enhanced Line SEgment Drawing

ELSED: Enhanced Line SEgment Drawing This repository contains the source code of ELSED: Enhanced Line SEgment Drawing the fastest line segment detecto

Iago Suárez 125 Dec 31, 2022
Automatic Attendance marker for LMS Practice School Division, BITS Pilani

LMS Attendance Marker Automatic script for lazy people to mark attendance on LMS for Practice School 1. Setup Add your LMS credentials and time slot t

Nihar Bansal 3 Jun 12, 2021
Pyramid Pooling Transformer for Scene Understanding

Pyramid Pooling Transformer for Scene Understanding Requirements: torch 1.6+ torchvision 0.7.0 timm==0.3.2 Validated on torch 1.6.0, torchvision 0.7.0

Yu-Huan Wu 119 Dec 29, 2022
Deep Latent Force Models

Deep Latent Force Models This repository contains a PyTorch implementation of the deep latent force model (DLFM), presented in the paper, Compositiona

Tom McDonald 5 Oct 26, 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