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Official pytorch implementation of ICML2025 "TAROT: Targeted Data Selection via Optimal Transport"

TAROT 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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# TAROT: Targeted Data Selection via Optimal Transport
[Lan Feng](https://alan-lanfeng.github.io/), [Fan Nie](https://scholar.google.com/citations?user=o2lsU8YAAAAJ&hl=en), [Yuejiang Liu](https://sites.google.com/view/yuejiangliu/home), [Alexandre Alahi](https://people.epfl.ch/alexandre.alahi?lang=en)

[Visual Intelligence for Transportation Lab, EPFL](https://www.epfl.ch/labs/vita/)

Stanford University

[**Paper**](https://arxiv.org/pdf/2412.00420)

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<img align="center" src="docs/assets/pull.png" alt="System Overview" width="500">
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---

## 🛠 Environment Setup

To get started with TAROT, follow these steps:
   - Install [GeomLoss](https://www.kernel-operations.io/geomloss/).  
   - Install [Trak](https://trak.readthedocs.io/en/latest/).

---

## 🚀 Quick Start

### 🚗[Motion Prediction](./examples/motion_prediction/README.md)

### 📖[Instruction Tuning](./examples/motion_prediction/README.md)

### 🏞️[Semantic Segmentation](./examples/motion_prediction/README.md)

## 📊Qualitative Results of WFD
![system](https://raw.githubusercontent.com/vita-epfl/TAROT/main/docs/assets/inf.png)

## Acknowledgement
This repo relies on the [TRAK](https://trak.readthedocs.io/en/latest/) implementation to compute the projected gradients. We are immensely grateful to the authors of that project.

## For citation:

```
@article{feng2024tarot,
  title={TAROT: Targeted Data Selection via Optimal Transport},
  author={Feng, Lan and Nie, Fan and Liu, Yuejiang and Alahi, Alexandre},
  journal={arXiv preprint arXiv:2412.00420},
  year={2024}
}

TAROT

TAROT 최신버젼 다운로드

오늘의 추천 프로젝트

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TAROT 최신버젼 다운로드

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