Source code for Neural Information Processing Systems (NeurIPS) 2018 paper "Multi-Task Learning as Multi-Objective Optimization"

Multi-task learning using uncertainty to weigh losses for scene geometry and semantics, Auxiliary Tasks in Multi-task Learning

The official repository for DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image Segmentation.

Masked AutoEncoders leveraging Segment-Anything

Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization

[CVPR 2024 Highlight] Style Injection in Diffusion: A Training-free Approach for Adapting Large-scale Diffusion Models for Style Transfer

Unofficial pytorch implementation of 'Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization' [Huang+, ICCV2017]

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

Python implementation of "Region Filling and Object Removal" by A. Criminisi et al.

This repository is for the first comprehensive survey on Meta AI's Segment Anything Model (SAM).

A collection of project, papers, and source code for Meta AI's Segment Anything Model (SAM) and related studies.

This repo contains the implementation of the Wasserstein Barycenter Transport proposed in "Wasserstein Barycenter Transport for Acoustic Adaptation" at ICASSP21 and "Wasserstein Barycenter for Mult…

Optimal transport tools implemented with the JAX framework, to get differentiable, parallel and jit-able computations.

digits experiments SVHN->MNIST of implicit alignment with DANN

Code to reproduce the results from the paper "Optimal Transport for Multi-source Domain Adaptation under Target Shift"

Code for "Margin-aware Adversarial Domain Adaptation with Optimal Transport" paper

Functional Optimal Transport: Map Estimation and Domain Adaptation for Functional data

Official Python3 implementation of our ICML 2021 paper "Unbalanced minibatch Optimal Transport; applications to Domain Adaptation"

Implementation of paper multi-source distilling domain adaptation

Official repository of "Minibatch optimal transport distances; analysis and applications" (https://arxiv.org/pdf/2101.01792.pdf)

Sliced Wasserstein Distance (SWD) in PyTorch

Implementation of Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation (ECCV 2020).

Source code of our submission (Rank 1) for Multi-Source Domain Adaptation task in VisDA-2019

Code for ICML2020 "Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation"

Code release for "Conditional Adversarial Domain Adaptation" (NIPS 2018)

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

Code for CVPR-2019 paper "Progressive Feature Alignment for Unsupervised Domain Adaptation"