基于 bert4keras 的一个baseline 不作任何 数据trick 单模 线上 最高可到 0.7891 # 基础 版 train.py 0.7769 # transformer 各层 cls concat 明神的trick https://xv44586.github.io/2021/01/20/ccf-qa-2/ train_concat.py 0.7786 # 使用那个FGM对抗 train_FGM.py 0.7891 # 苏神提出的 PET train_PET.py 0.7812 预训练模型使用 nezha 使用说明: 数据放在 data下 下载预训练模型解压 模型会保存在 train中 优化方向: 1,融合🙃 bert4keras >= 0.10.0 nezha的预训练模型 链接: https://pan.baidu.com/s/1lURyXs39PYnsb4imCjVkfQ 密码: 1eqq --来自百度网盘超级会员V4的分享
“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
Overview
Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments
Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments Paper: arXiv (ICRA 2021) Video : https://youtu.be/CC
Code and data for the paper "Hearing What You Cannot See"
Hearing What You Cannot See: Acoustic Vehicle Detection Around Corners Public repository of the paper "Hearing What You Cannot See: Acoustic Vehicle D
This repo contains implementation of different architectures for emotion recognition in conversations.
Emotion Recognition in Conversations Updates 🔥 🔥 🔥 Date Announcements 03/08/2021 🎆 🎆 We have released a new dataset M2H2: A Multimodal Multiparty
Pytorch implementation for the Temporal and Object Quantification Networks (TOQ-Nets).
TOQ-Nets-PyTorch-Release Pytorch implementation for the Temporal and Object Quantification Networks (TOQ-Nets). Temporal and Object Quantification Net
PyTorch Implementation of DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs
DiffGAN-TTS - PyTorch Implementation PyTorch implementation of DiffGAN-TTS: High
This repo holds code for TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
TransUNet This repo holds code for TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation Usage
Calibrated Hyperspectral Image Reconstruction via Graph-based Self-Tuning Network.
mask-uncertainty-in-HSI This repository contains the testing code and pre-trained models for the paper Calibrated Hyperspectral Image Reconstruction v
Code for WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models.
WECHSEL Code for WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models. arXiv: https://arx
A Multi-modal Perception Tracker (MPT) for speaker tracking using both audio and visual modalities
MPT A Multi-modal Perception Tracker (MPT) for speaker tracking using both audio and visual modalities. Implementation for our AAAI 2022 paper: Multi-
Towards Interpretable Deep Metric Learning with Structural Matching
DIML Created by Wenliang Zhao*, Yongming Rao*, Ziyi Wang, Jiwen Lu, Jie Zhou This repository contains PyTorch implementation for paper Towards Interpr
Modifications of the official PyTorch implementation of StyleGAN3. Let's easily generate images and videos with StyleGAN2/2-ADA/3!
Alias-Free Generative Adversarial Networks (StyleGAN3) Official PyTorch implementation of the NeurIPS 2021 paper Alias-Free Generative Adversarial Net
This is a collection of our NAS and Vision Transformer work.
This is a collection of our NAS and Vision Transformer work.
Boosted CVaR Classification (NeurIPS 2021)
Boosted CVaR Classification Runtian Zhai, Chen Dan, Arun Sai Suggala, Zico Kolter, Pradeep Ravikumar NeurIPS 2021 Table of Contents Quick Start Train
Deep Anomaly Detection with Outlier Exposure (ICLR 2019)
Outlier Exposure This repository contains the essential code for the paper Deep Anomaly Detection with Outlier Exposure (ICLR 2019). Requires Python 3
Image Segmentation with U-Net Algorithm on Carvana Dataset using AWS Sagemaker
Image Segmentation with U-Net Algorithm on Carvana Dataset using AWS Sagemaker This is a full project of image segmentation using the model built with
NeuralWOZ: Learning to Collect Task-Oriented Dialogue via Model-based Simulation (ACL-IJCNLP 2021)
NeuralWOZ This code is official implementation of "NeuralWOZ: Learning to Collect Task-Oriented Dialogue via Model-based Simulation". Sungdong Kim, Mi
System-oriented IR evaluations are limited to rather abstract understandings of real user behavior
Validating Simulations of User Query Variants This repository contains the scripts of the experiments and evaluations, simulated queries, as well as t
Header-only library for using Keras models in C++.
frugally-deep Use Keras models in C++ with ease Table of contents Introduction Usage Performance Requirements and Installation FAQ Introduction Would
Code for Subgraph Federated Learning with Missing Neighbor Generation (NeurIPS 2021)
To run the code Unzip the package to your local directory; Run 'pip install -r requirements.txt' to download required packages; Open file ~/nips_code/
Official implementation of CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21
CATs: Cost Aggregation Transformers for Visual Correspondence NeurIPS'21 For more information, check out the paper on [arXiv]. Training with different