526互联

样本zero-shot learning zero

About Spoken word poetry-----Learning journals6

In this world, poetry has many forms of expression, short and long, written on paper or carved on walls, but this time our focus is on Spoken word poe ......
journals6 Learning journals Spoken poetry

About Spoken word poetry-----Learning journals 6

In this world, poetry has many forms of expression, short and long, written on paper or carved on walls, but this time our focus is on Spoken word poe ......
Learning journals Spoken poetry About

About spoken word poetry----Learning journals 6

In this world, poetry has many forms of expression, short and long, written on paper or carved on walls, but this time our focus is on Spoken word poe ......
Learning journals spoken poetry About

Do you know the bitwise sum sample demonstrated in "Neural Networks and Deep Learning" by autor Michael Nielsen?

Do you know the bitwise sum sample demonstrated in "Neural Networks and Deep Learning" by autor Michael Nielsen? Yes, I am familiar with the bitwise s ......
quot demonstrated Networks Learning bitwise

论文阅读笔记《Sim-to-real learning for bipedal locomotion under unsensed dynamic loads》

发表于ICRA 2022 无感知动态负载下双足运动的虚实迁移学习 ### 背景 机器人携带负载时的运动控制问题还没有得到充分的研究，尤其是动态负载。 在这项工作中，我们特别感兴趣的是动态载荷，比如一个附加的推车或液体容器，而不是简单的静态载荷，比如刚性附着的固定质量。 ......
Sim-to-real locomotion learning unsensed bipedal

EECS 280 Project 5: Machine Learning

EECS 280 Project 5: Machine LearningDue 8:00pm Tuesday April 18, 2023. You may work alone or with a partner (partnership guidelines).Winter 2023 relea ......
Learning Project Machine EECS 280

GNN-learning-notes

GNN 学习笔记 Datetime: 2023-04-01T16:28+08:00 Categories: MachineLearning 初学者一定要看：【GNN 入门】综述篇 - 知乎用户 MxLVSX 的文章 - zhihu.com，包括频域和空域、任务类型、经典模型。 最早的 GNN，介于迭 ......
GNN-learning-notes learning notes GNN

11 zkrpChain Towards multi-party privacy-preserving data auditing for consortium blockchains based on zero-knowledge range proofs

![](https://img2023.cnblogs.com/blog/1954056/202304/1954056-20230407170611339-1868056177.png)![](https://img2023.cnblogs.com/blog/1954056/202304/19540... ......
privacy-preserving zero-knowledge multi-party blockchains consortium

迁移学习《Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks》

论文信息 论文标题：Pseudo-Label : The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks论文作者：Dong-Hyun Lee论文来源：2013——ICML论文地址：downlo ......
Semi-Supervised Pseudo-Label Supervised Efficient Learning

【论文笔记 - InstructPix2Pix】InstructPix2Pix: Learning to Follow Image Editing Instructions

InstructPix2Pix和Pix2Pix是两码事。Pix2Pix使用的是GAN，而InstructPix2Pix使用的是Diffusion。鉴于目前图像生成与预训练大模型的飞速发展，即便是CycleGAN里所谓的“不可获取的”成对的数据，也可以通过预训练模型生成出来，作为数据集进行训练。Ins... ......
InstructPix2Pix InstructPix2 InstructPix 2Pix Instructions

FATE Machine Learning

OFFICE 280FATE Machine LearningCRISTIáN BRAVOOFFICE 280This week… Fairness Definition of Fairness Confounding Transparency and Explainability Shapley ......
Learning Machine FATE

Learning with Mini-Batch

我们采取一种折衷的想法，即取一部分数据，作为全部数据的代表，让神经网络从这每一批数据中学习，这里的“一部分数据”称为mini-batch，这种方法称为mini-batch学习。 ......
Mini-Batch Learning Batch with Mini

【Deep Learning】DDPM

DDPM 1. 大致流程 1.1 宏观流程 1.2 训练过程 1.3 推理过程 2. 对比GAN 2.1 GAN流程 2.2 相比GAN优点 训练过程更稳定，损失函数指向性更强（loss数值大小指示训练效果好坏） 3. 详细流程 3.1 扩散阶段 如下图，X0为初始干净图像，XT由X0逐步添加噪声所 ......
Learning Deep DDPM

【Deep Learning】L1 Loss、L2 Loss、Smooth L1 Loss

L1 Loss、L2 Loss、Smooth L1 Loss L1 Loss L1 Loss别称：L1 范数损失、最小绝对值偏差（LAD）、最小绝对值误差（LAE）。最常看到的MAE也是指L1 Loss。它是把目标值与模型输出（估计值）做绝对值得到的误差。 什么时候使用？ 回归任务简单的模型由于神经 ......
Loss Learning Smooth Deep L1

m基于CNN卷积网络和GEI步态能量图的步态识别算法MATLAB仿真,测试样本采用现实拍摄的场景进行测试,带GUI界面

1.算法描述 目前关于步态识别算法研究主要有两种：基于模型的方法和非基于模型的方法。基于模型的步态识别方法优点在于能够很好的体现步态图像序列当前的变化，也能够预测过去和未来的状态。基于非模型的方法是通过对步态相关特征进行预测来建立相邻帧间的关系，其中特征包括位置、速度、形状等，其中基于形状特征的方法 ......
步态 卷积 样本 算法 能量

迁移学习（DCCL）《Domain Confused Contrastive Learning for Unsupervised Domain Adaptation》

论文信息 论文标题：Domain Confused Contrastive Learning for Unsupervised Domain Adaptation论文作者：Quanyu Long, Tianze Luo, Wenya Wang and Sinno Jialin Pan论文来源：NAA ......
Domain Unsupervised Contrastive Adaptation Confused

异常检测-1-综述-Deep Learning for Anomaly Detection: A Survey

https://www.researchgate.net/publication/330357393_Deep_Learning_for_Anomaly_Detection_A_Survey?enrichId=rgreq-40000b66a80039399492f90066ec07a0-XXX&en ......
Detection Learning Anomaly Survey Deep

Online Continual Learning with Maximally Interfered Retrieval---阅读笔记

Online Continual Learning with Maximally Interfered Retrieval 阅读笔记 摘要： 本文主要提出了一种可控的样本采集策略的重放方法。我们检索受干扰最大的样本，即它们的预测将受到预测参数更新的最大负面影响。 1 Introduction 人工神 ......
Interfered Continual Maximally Retrieval Learning

【论文精读 - DDPM】Deep Unsupervised Learning using Nonequilibrium Thermodynamics

数学推导【转载】 数学推导过程来自苏剑林大神的《生成扩散模型漫谈》系列，感谢苏神的无私奉献，让我这样数学功底不好的人也能领略这个当下最为火爆的模型的精髓。 系列中有部分步骤，一眼看过去可能有些费解，所以这里稍微做了展开，作为自己的笔记用。 通俗解释：DDPM=拆楼+建楼 生成模型实际上就是：随机噪声 ......
Nonequilibrium Thermodynamics Unsupervised Learning 论文

06.Sentiment Analysis Based on Deep Learning: A Comparative Study

Sentiment Analysis Based on Deep Learning: A Comparative Study 深度学习的情感分析的比较研究 目前在社交网络中的情绪分析已经成为了解用户意见的有力手段，并有着广泛应用。然而情感分析的效率和准确性受到自然语言处理中遇到的挑战和障碍 本问综述 ......
Comparative Sentiment Analysis Learning Based

The Predictron: End-To-End Learning and Planning

**发表时间：**2017（ICML 2017） **文章要点：**这篇文章设计了一个叫Predictron的结构，在abstract的状态上进行学习，通过multiple planning depths来使得model self-consistent，进行端对端的学习。这里的设定是MRP，不是MD ......
Predictron End-To-End End Learning Planning

20230402 Zero-Knowledge Proof

https://zhuanlan.zhihu.com/p/144847471 零知识证明想要解决的问题是，让一方向另一方证明他知道某个问题的答案但却不想透露该问题的具体答案。是不是有种贱贱的感觉？ https://blog.csdn.net/qq_35739903/article/details/1 ......
Zero-Knowledge Knowledge 20230402 Proof Zero

Learning Blender: A Hands-On Guide to Creating 3D Animation(2nd Edition)

参考1：https://www.doc88.com/p-9975664843996.html（书） 参考2：https://www.bilibili.com/video/BV1wW411i7nY（视频） ......
Animation Learning Hands-On Creating Blender

mini spring learning

https://www.pexels.com/zh-cn/photo/768089/ http://www.implements.fun:8080/tag/minispring package com.minis.beans.factory; import com.minis.beans.Beans ......
learning spring mini

About Interviews and Learning------Learning journals 5

This week, we produced a group assignment, an interview video on cultural appropriation and appreciation, from which we can always learn something use ......
Learning Interviews journals About and

learn C++ for infrastructure software

To learn C++ for infrastructure software, you can follow these steps: Learn the basics of C++: Start by learning the basics of C++ programming languag ......
infrastructure software learn for

Float 或者 Double 除以零不会抛出 java.lang.ArithmeticExceptionL:/by zero 异常

1. Java 的浮点运算是基于 IEEE-754 标准来的。 IEEE-754 standard Java's Floating-Point Operations 2. Java 语言规范 https://docs.oracle.com/javase/specs/jls/se7/html/jls- ......
ArithmeticExceptionL Double Float java lang

计算机视觉中的主动学习（Active Learning）介绍

前言 Active Learning主动学习是机器学习 (ML) 的一个研究领域，旨在通过以智能方式查询管道的下一个数据来降低构建新机器学习解决方案的成本和时间。在开发新的 AI 解决方案和处理图像、音频或文本等非结构化数据时，我们通常需要人工对数据进行注释，然后才能使用它们来训练我们的模型。这个数 ......
Learning 视觉 计算机 Active

转：np.zeros()函数

函数调用方法： numpy.zeros(shape, dtype=float) 各个参数意义：shape：创建的新数组的形状（维度）。dtype：创建新数组的数据类型。返回值：给定维度的全零数组。 基础用法： import numpy as np array = np.zeros([2, 3]) p ......
函数 zeros np

Sample-Based Learning and Search with Permanent and Transient Memories

**发表时间：**2008（ICML 2008） **文章要点：**这篇文章提出Dyna-2算法，把sample-based learning and sample-based search结合起来，并在Go上进行测试。作者认为，search算法是一种transient的算法，就是短期记忆用了就忘了 ......
Sample-Based Permanent and Transient Learning
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