[NeurIPS 2021] The PyTorch implementation of paper "Self-Supervised Learning Disentangled Group Representation as Feature"

Last update: Dec 24, 2022

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IP-IRM

[NeurIPS 2021] The PyTorch implementation of paper "Self-Supervised Learning Disentangled Group Representation as Feature". Codes will be released recently.

If you find our codes helpful, please cite our paper:

@inproceedings{wang2021self,
  title={Self-Supervised Learning Disentangled Group Representation as Feature},
  author={Wang, Tan and Yue, Zhongqi and Huang, Jianqiang and Sun, Qianru and Zhang, Hanwang},
  booktitle={Conference and Workshop on Neural Information Processing Systems (NeurIPS)},
  year={2021}
}

Owner

Wang Tan

Ph.D. student of MreaL Lab, NTU

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[NeurIPS 2021] The PyTorch implementation of paper "Self-Supervised Learning Disentangled Group Representation as Feature"

Related tags

Overview

IP-IRM

Owner

Wang Tan

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[NeurIPS 2021] The PyTorch implementation of paper "Self-Supervised Learning Disentangled Group Representation as Feature"

Related tags

Overview

IP-IRM

Owner

Wang Tan

“英特尔创新大师杯”深度学习挑战赛 赛道3：CCKS2021中文NLP地址相关性任务

Model Quantization Benchmark

External Attention Network

BlockUnexpectedPackets - Preventing BungeeCord CPU overload due to Layer 7 DDoS attacks by scanning BungeeCord's logs

Pytorch implementation for our ICCV 2021 paper "TRAR: Routing the Attention Spans in Transformers for Visual Question Answering".

Dynamic Realtime Animation Control

Independent and minimal implementations of some reinforcement learning algorithms using PyTorch (including PPO, A3C, A2C, ...).

Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"

The Python code for the paper A Hybrid Quantum-Classical Algorithm for Robust Fitting

This repository is an implementation of our NeurIPS 2021 paper (Stylized Dialogue Generation with Multi-Pass Dual Learning) in PyTorch.

A Simple Example for Imitation Learning with Dataset Aggregation (DAGGER) on Torcs Env

The PyTorch implementation for paper "Neural Texture Extraction and Distribution for Controllable Person Image Synthesis" (CVPR2022 Oral)

Pytorch implementation of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net.

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Semi-supervised semantic segmentation needs strong, varied perturbations

rliable is an open-source Python library for reliable evaluation, even with a handful of runs, on reinforcement learning and machine learnings benchmarks.

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