representation
[论文阅读] Self-conditioned Image Generation via Generating Representations
Pre title: Self-conditioned Image Generation via Generating Representations accepted: arXiv 2023 paper: https://arxiv.org/abs/2312.03701 code: https:/ ......
Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods
目录概符号说明Cold Brew代码 Zheng W., Huang E. W., Rao N., Katariya S., Wang Z., Subbian K. Cold brew: Distilling graph node representations with incomplete or ......
[论文阅读] Learning Component-Level and Inter-Class Glyph Representation for few-shot Font Generation
Pre title: Learning Component-Level and Inter-Class Glyph Representation for few-shot Font Generation accepted: ICME 2023 paper: https://ieeexplore.ie ......
Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation；OCRNet
Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation * Authors: [[Yuhui Yuan]], [[Xiaokang Chen]], [[Xilin Chen]], [[ ......
Drug response prediction using graph representation learning and Laplacian feature selection
Drug response prediction using graph representation learning and Laplacian feature selection Minzhu Xie 1 2, Xiaowen Lei 3, Jianchen Zhong 3, Jianxing ......
DeepWalk Online Learning of Social Representations
目录概符号说明DeepWalk代码 Perozzi B., AI-Rfou R. and Skiena S. DeepWalk: Online learning of social representations. KDD, 2014. 概 经典的 graph embedding 学习方法. 符号说 ......
【今日收获】Representation Collapse
在深度学习中，对预训练模型进行 fine-tuning 可能会引发一种称为 "Representation Collapse" 的现象。Representation Collapse 指的是模型在 fine-tuning 过程中失去了原始预训练模型所具有的多样性和丰富性的特征表示，导致最终模型的表示 ......
BMR论文阅读笔记（Bootstrapping Multi-view Representations for Fake News Detection）
以往的多媒体假新闻检测研究包括一系列复杂的特征提取和融合网络，从新闻中收集有用的信息。然而，跨模态一致性如何影响新闻的保真度以及不同模态的特征如何影响决策仍然是一个悬而未决的问题。本文提出了一种基于自举多视图表示(BMR)的假新闻检测方案。对于一篇多模态新闻，我们分别从文本、图像模式和图像语义的角度... ......
2023ICCV_Feature Modulation Transformer: Cross-Refinement of Global Representation via High-Frequency Prior for Image Super-Resolution
一. Motivation 1. transformer的工作主要集中在设计transformer块以获得全局信息，而忽略了合并高频先验的潜力 2. 关于频率对性能的影响的详细分析有限（Additionally, there is limited detailed analysis of the i ......
CA-TCC: 半监督时间序列分类的自监督对比表征学习《Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification》(时间序列、时序表征、时间和上下文对比、对比学习、自监督学习、半监督学习、TS-TCC的扩展版)
现在是2023年11月27日，10:48，今天把这篇论文看了。 论文：Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series Classification GitHub：https://g ......
通过时序和上下文对比学习时间序列表征《Time-Series Representation Learning via Temporal and Contextual Contrasting》(时间序列、时序表征、时态和上下文对比、对比学习、自监督学习、半监督学习)
现在是2023年11月14日的22:15，肝不动了，要不先回寝室吧，明天把这篇看了，然后把文档写了。OK，明天的To Do List. 现在是2023年11月15日的10:35，继续。 论文：Time-Series Representation Learning via Temporal and C ......
doris FE启动异常：org.yaml.snakeyaml.representer.Representer: method <init>()V not found
doris FF启动异常，异常信息如下： 2023-11-01 09:53:22,691 INFO (main|1) [PaloFe.start():124] Palo FE starting... 2023-11-01 09:53:22,699 INFO (main|1) [FrontendOpt ......
【图形学笔记】Lecture09-Mesh Representation &Geometry Processing-网格表示与几何处理
Lecture09-Mesh Representation &Geometry Processing-网格表示与几何处理 目录Lecture09-Mesh Representation &Geometry Processing-网格表示与几何处理Mesh Presentation网格表示Smooth ......
Robust Graph Representation Learning via Neural Sparsification
目录概符号说明NeuralSparse Zheng C., Zong B., Cheng W., Song D., Ni J., Yu W., Chen H. and Wang W. Robust graph representation learning via neural sparsifica ......
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation 关键词：GRU、Encoder-Decoder 📜 研究主题 提出了Encoder-Decoder结构，采用两 ......
Non-terminating decimal expansion; no exact representable decimal result.
上网查了一下这个异常的，找到了原因所在：通过BigDecimal的divide方法进行除法时当不整除，出现无限循环小数时，就会抛异常：java.lang.ArithmeticException: Non-terminating decimal expansion; no exact represen ......
Implicit Autoencoder for Point-Cloud Self-Supervised Representation Learning论文阅读
2023 ICCV Implicit Autoencoder for Point-Cloud Self-Supervised Representation Learning论文阅读，思想很妙，该笔记非常简要 ......
[NIPS 2021]Do Transformers Really Perform Bad for Graph Representation
[NIPS 2021]Do Transformers Really Perform Bad for Graph Representation 微软提出的graph transformer，名叫Graphormer Transformer 通常，transformer layer有一个self-att ......
Learning Continuous Image Representation with Local Implicit Image Function
Learning Continuous Image Representation with Local Implicit Image Function（阅读笔记）11.03 局部隐式图像函数（LIIF）表示连续中的图像，可以以任意高分辨率表示。 摘要：如何表示图像？当视觉世界以连续的方式呈现时，机器 ......
Unsupervised Degradation Representation Learning f
Unsupervised Degradation Representation Learning for Blind Super-Resolution文献阅读 (2022.09.28)盲超分辨率的退化表征（向量）学习 摘要：大多数基于CNN的SR都是基于退化固定且可知这一假设。但是实际退化和假设不一 ......
EVA: Visual Representation Fantasies from BAAI
本文做个简单总结，博主不是做自监督领域的，如果错误，欢迎指正。 链接 Code： Official：baaivision/EVA MMpretrain：open-mmlab/mmpretrain/tree/main/configs/eva02 Paper： EVA01：EVA: Explorin ......
[论文阅读] Momentum contrast for unsupervised visual representation learning
# Momentum contrast for unsupervised visual representation learning ## Introduction 我们提出了动量对比（MoCo）作为一种构建具有对比损失的无监督学习的大型一致字典的方法（图1）。 我们将字典维护为数据样本队列：当前 ......
论文解读（WDGRL）《Wasserstein Distance Guided Representation Learning for Domain Adaptation》
Note：[ wechat：Y466551 | 可加勿骚扰，付费咨询 ] 论文信息 论文标题：Wasserstein Distance Guided Representation Learning for Domain Adaptation论文作者：Jian Shen、Yanru Qu、Weinan ......
bert，Bidirectional Encoder Representation from Transformers
BERT的全称是Bidirectional Encoder Representation from Transformers，是Google2018年提出的预训练模型，即双向Transformer的Encoder，因为decoder是不能获要预测的信息的。模型的主要创新点都在pre-train方法上 ......
Bidirectional Encoder Representations from Transformers
BERT（Bidirectional Encoder Representations from Transformers）是由Google在2018年提出的自然语言处理（NLP）模型。它是一个基于Transformer架构的预训练模型，通过无监督学习从大量的文本数据中学习通用的语言表示，从而能够更好... ......
RESTful API（Representational State Transfer API）是一种设计和构建网络应用程序的软件架构风格。它是一种基于HTTP协议的API设计理念，旨在实现系统的可伸缩性、简洁性、可靠性和可扩展性。
RESTful API（Representational State Transfer API）是一种设计和构建网络应用程序的软件架构风格。它是一种基于HTTP协议的API设计理念，旨在实现系统的可伸缩性、简洁性、可靠性和可扩展性。 RESTful API 的设计原则可以概括为以下几点： **资源* ......
Self-attention with Functional Time Representation Learning
[TOC] > [Xu D., Ruan C., Kumar S., Korpeoglu E. and Achan K. Self-attention with functional time representation learning. NIPS, 2019.](http://arxiv.or ......
论文阅读 | Soteria: Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective
Soteria:基于表示的联邦学习中可证明的隐私泄露防御https://ieeexplore.ieee.org/document/9578192 # 3 FL隐私泄露的根本原因 ## 3.1 FL中的表示层信息泄露 **问题设置** 在FL中，有多个设备和一个中央服务器。服务器协调FL进程，其中每个 ......
Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation
[TOC] > [Qiu R., Huang Z., Ying H. and Wang Z. Contrastive learning for representation degeneration problem in sequential recommendation. WSDM, 2022.] ......
ARC060D - Best Representation
诈骗题。给了个模数但是答案根本达不到那个级别。 先提前给出一个引理，如果长度为 $2n$ 的 $s$ 有 $s[1,n]=s[n+1,2n]$ 并且 $s[1,m]=s[m+1,2m](mn-x$，那么就有最左边和最右边的 $n-border$ 串相等。两个拼起来，根据引理就有更小的循环节，这是不被 ......