bayes-adaptive meta-learning adaptive learning

论文：Predicting Optical Water Quality Indicators from Remote Sensing Using Machine Learning Algorithms in Tropical Highlands of Ethiopia

水刊，中科院都没有收录。不属于sci。吃一堑长一智，以后先看属于哪个期刊的。总是忘记。期刊：Hydrology 浪费时间，啥也没有，没有创新点，就一点点的对比工作量。 “Predicting Optical Water Quality Indicators from Remote Sensing ......

Predicting Indicators Algorithms Highlands Ethiopia更新时间 2023-11-29

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 ......

时间序列时间序列 supervised 时序更新时间 2023-11-28

The Hello World of Deep Learning with Neural Networks

The Hello World of Deep Learning with Neural Networks dlaicourse/Course 1 - Part 2 - Lesson 2 - Notebook.ipynb at master · lmoroney/dlaicourse (github ......

Learning Networks Neural Hello World更新时间 2023-11-28

The Hello World of Deep Learning with Neural Networks

The Hello World of Deep Learning with Neural Networks dlaicourse/Course 1 - Part 2 - Lesson 2 - Notebook.ipynb at master · lmoroney/dlaicourse (github ......

Learning Networks Neural Hello World更新时间 2023-11-28

《Visual Analytics for RNN-Based Deep Reinforcement Learning》

摘要准备开题报告，整理一篇 2022 年TOP 论文。论文介绍该论文是一篇 2022 年，有关可视化分析基于RNN 的深度强化学习训练过程的文章。一作是 Junpeng Wang ，作者主要研究领域就是：visualization, visual analytics, explainable ......

Reinforcement Analytics RNN-Based Learning Visual更新时间 2023-11-28

Can Pre-Trained Text-to-Image Models Generate Visual Goals for Reinforcement Learning

概述 Learning form the Void (LfVoid) 根据给定的language instruction对observation进行appearance-based and structure-based修改得到goal images，为RL提供奖励信号。提升了example-bas ......

Text-to-Image Reinforcement Pre-Trained Generate Learning更新时间 2023-11-28

Computer vision: models, learning and inference

http://www.computervisionmodels.com/ 13.2.3 SIFT detector SIFT 尺度不变特征转换 s a second method for identifying interest points 一个尺度和对应兴趣点定位 14 15 16 ......

inference Computer learning vision models更新时间 2023-11-28

Learn DevOps 第二章：Start DevOps with Docker（一）

一、Introduction and installation 这一张让我们来看一些让开发运维变得非常简单的东西：Containerization。我们身处微服务的世界，有数百个微服务，一些用Java构建，一些用python构建，还有一些可能是用Javascript构建的。这三种语言的应用程序所需 ......

DevOps 第二章 Docker Learn Start更新时间 2023-11-28

Federated Learning005

联邦学习——笔记005 2023.11.27周一，最近支原体肺炎高发。研一上课结了一部分，赶紧看论文。时隔大半年，今天开始学习联邦学习的大综述————Advances and Open Problems in Federated Learning（联邦学习中的最新进展和开放问题） Introduc ......

Federated Learning 005更新时间 2023-11-27

offline RL | BCQ：学习 offline dataset 的 π(a|s)，直接使用 (s, π(s)) 作为 Q learning 训练数据

① 使用 VAE 建模 offline dataset 的 π(a|s)，② 添加一个可以学习的 action 扰动 ξ，③ 用 (s, a=π(s)+ξ, r, s') 做 Q-learning。 ......

offline learning dataset 数据 BCQ更新时间 2023-11-27

Java learning Day2 常量变量运算符 Scanner 方法数组

常量：字面值常量（直接写值的常量）+自定义常量变量： long型变量后必须加L; 小数字面值常量默认double 若用float需加F；变量强转：小的会自动转成大的 float虽然只有4个字节但是比所有整型的取值范围都大浮点型有精度问题表达式类型提升：如果表达式当中存在多种数据类型 ......

运算符常量数组变量 learning更新时间 2023-11-26

Learning Auxiliary Monocular Contexts Helps Monocular 3D Object Detection (5)

Qualitative Results如下图所示: ......

Monocular Auxiliary Detection Learning Contexts更新时间 2023-11-26

Learning Graph Filters for Spectral GNNs via Newton Interpolation

目录概符号说明MotivationNewtonNet代码 Xu J., Dai E., Luo D>, Zhang X. and Wang S. Learning graph filters for spectral gnns via newton interpolation. 2023. 概令谱 ......

Interpolation Learning Spectral Filters Newton更新时间 2023-11-26

How Can South Asia Adapt Integrated River Basin Management to Its Soil Erosion

Due to the instability of the monsoon, floods and droughts are frequent in South Asia, resulting in severe soil erosion. Every year, South Asia suffer ......

Integrated Management Erosion Adapt Basin更新时间 2023-11-26

Adaptive Sparse Pairwise Loss for Object Re-Identification

https://blog.csdn.net/amusi1994/article/details/130037400 triplet loss中需要计算每个样本之间的距离，从而计算出loss，作者认为同一类的某些样本可能存在有害的信息，所以不应该将所有样本都用于计算loss。作者提出的SP loss中 ......

Re-Identification Identification Adaptive Pairwise Sparse更新时间 2023-11-24

Java Learning Day1 关键字、标识符、注释、变量

其实之前也学习过两个月的JAVA，跟着淘宝上买的王道Java课，每天看了1day，整个过程下来感觉什么都没有掌握，所以现在就打算重新学一次，从最开始的关键字开始，也就开通了博客，希望这次学习可以多多掌握一些吧。关键字：小写、含有特殊含义的单词标识符：方法名、类名、参数名、变量名（英文、不用拼音） ......

标识符注释变量标识 Learning更新时间 2023-11-24

Joint Autoregressive and Hierarchical Priors for Learned Image Compression

abstruct 最近的图像压缩模型基于自编码器，学习近似可逆的映射（从像素到量化的可逆表示），这些与熵模型（潜在表示的先验）结合，可以与标准算术编码算法一起使用产生压缩比特流。与简单的全因子先验相比，分层熵模型可以利用更多潜变量中的结构，从而在保存端到端优化的同时提高压缩性能。众所周知，自回归模型 ......

Autoregressive Hierarchical Compression Learned Priors更新时间 2023-11-23

【略读论文|时序知识图谱补全】Learn from Relational Correlations and Periodic Events for Temporal Knowledge Graph Reasoning

会议：SIGIR，时间：2023，学校：国防科技大学摘要：之前模型存在的问题：未能利用快照内结构信息的关系之间的语义相关性与快照间时间交互沿时间轴的周期性时间模式。本文的工作：提出了一种新的推理模型（RPC）；它通过两个新的通信单元，即关系通信单元(RCU)和周期通信单元(PCU)，充分挖掘关 ......

时序图谱 Correlations Relational Knowledge更新时间 2023-11-23

论文阅读笔记：Revisiting Prototypical Network for Cross Domain Few-Shot Learning

标题：重新审视用于跨领域少样本学习的原型网络研究背景：问题背景：原型网络是一种流行的小样本学习方法，其网络简单而直观，对于小样本学习问题有着较好的表现，尤其是在图像分类等领域。存在问题：然而，当推广到跨领域的少样本分类任务时，其性能出现了大幅度下降，这严重限制了原型网络的实用性。研究动机： ......

Prototypical Revisiting Few-Shot Learning Network更新时间 2023-11-22

【略读论文|时序知识图谱补全】DREAM: Adaptive Reinforcement Learning based on Attention Mechanism for Temporal Knowledge Graph Reasoning

会议：SIGIR，时间：2023，学校：苏州大学计算机科学与技术学院，澳大利亚昆士兰布里斯班大学信息技术与电气工程学院，Griffith大学金海岸信息通信技术学院摘要：原因：现在的时序知识图谱推理方法无法生成显式推理路径，缺乏可解释性。方法迁移：由于强化学习 (RL) 用于传统知识图谱上的多跳 ......

时序图谱 Reinforcement Attention Knowledge更新时间 2023-11-21

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bayes-adaptive meta-learning adaptive learning

论文：Predicting Optical Water Quality Indicators from Remote Sensing Using Machine Learning Algorithms in Tropical Highlands of Ethiopia

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)

The Hello World of Deep Learning with Neural Networks

The Hello World of Deep Learning with Neural Networks

《Visual Analytics for RNN-Based Deep Reinforcement Learning》

Can Pre-Trained Text-to-Image Models Generate Visual Goals for Reinforcement Learning

Computer vision: models, learning and inference

Learn DevOps 第二章：Start DevOps with Docker（一）

Federated Learning005

offline RL | BCQ：学习 offline dataset 的 π(a|s)，直接使用 (s, π(s)) 作为 Q learning 训练数据

Java learning Day2 常量变量运算符 Scanner 方法数组

Learning Auxiliary Monocular Contexts Helps Monocular 3D Object Detection (5)

Learning Graph Filters for Spectral GNNs via Newton Interpolation

How Can South Asia Adapt Integrated River Basin Management to Its Soil Erosion

Adaptive Sparse Pairwise Loss for Object Re-Identification

Java Learning Day1 关键字、标识符、注释、变量

Joint Autoregressive and Hierarchical Priors for Learned Image Compression

【略读论文|时序知识图谱补全】Learn from Relational Correlations and Periodic Events for Temporal Knowledge Graph Reasoning

论文阅读笔记：Revisiting Prototypical Network for Cross Domain Few-Shot Learning

【略读论文|时序知识图谱补全】DREAM: Adaptive Reinforcement Learning based on Attention Mechanism for Temporal Knowledge Graph Reasoning

初中英语优秀范文100篇-003 My ways of learning English

【略读论文|时序知识图谱补全】Adaptive Path-Memory Network for Temporal Knowledge Graph Reasoning

【略读论文|时序知识图谱补全】Temporal Knowledge Graph Reasoning with Historical Contrastive Learning

Learning to rank: from pairwise approach to listwise approach

《Fine-Grained Image Analysis with Deep Learning: A Survey》阅读笔记

《Deep learning for fine-grained image analysis: A survey》阅读笔记

Literature Survey Slides of Paper Learning Dexterous In-Hand Manipulation

《A Survey on Deep Learning-based Fine-grained Object Classification and Semantic Segmentation》阅读笔记

Natural Image Reconstruction from fMRI using Deep Learning: A Survey

Dynamic Client Association for Energy-Aware Hierarchical Federated Learning