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1. Prompt-Tuning: 深度解读一种新的微调范式
2. 面向开发者的 ChatGPT 提示工程
3. IAIFI Summer School & Workshop
4. Git: submodule 子模块简明教程
5. GitHub 不再支持密码验证,如何在 macOS 上实现 Token 登陆配置
6. 解决 GitHub 的 host 域名被限制的问题
7. [Paper Summary] Complete Parameter Inference for GW150914 Using Deep Learning
8. Particle Swarm Optimization From Scratch Using Python
9. Bayes Inference, Bayes Factor, Model Selection
10. 谱分析 (spectral analysis) 的 SciPy 代码解析
11. Python 中负数取余问题
12. 恒 Q 变换 (Constant-Q transform)
13. Unit 3: Structure & Paragraphs(学术写作)
14. Python 装饰器之 Property: Setter 和 Getter
15. Unit 2: Verbs(学术写作)
16. Unit 1: Introduction; principles of effective writing(学术写作)
17. S 变换 (Stockwel transform)
18. Interactive GW simulation in JavaScript for NSs or BBHs
19. Linux/Unix 中 Screen 命令详解
20. 贝叶斯深度学习前沿进展 (朱军教授)
21. 深度学习: 从理论到算法 (王力威教授)
22. 累积引力波事件率图的 python 实现
23. Markdown Elements for Hugo/Wowchemy
24. 傅里叶变换算法及其 python 实现
25. Docker 简易入门教程
26. Ray Tutorial
27. 关于感受野 (Receptive field) 你该知道的事
28. Centos7/CUDA-9.2/cuDNN-7.3/MXNet-cu92/Floydhub 深度学习环境配置手册
29. CS231n课程资料:循环神经网络惊人的有效性
30. CS231n课程讲义翻译:神经网络3
31. CS231n课程讲义翻译:神经网络2
32. CS231n课程讲义翻译:神经网络1
33. CS231n课程讲义翻译:卷积神经网络
34. CS231n课程讲义翻译:反向传播
35. CS231n课程讲义翻译:最优化
36. CS231n课程讲义翻译:线性分类
37. CS231n课程讲义翻译:图像分类
38. Guest Lecture. Adversarial Examples and Adversarial Training
39. Guest Lecture. Efficient Methods and Hardware for Deep Learning
40. Lecture 14. Deep Reinforcement Learning
41. Lecture 13. Visualizing and Understanding
42. Lecture 12. Generative Models
43. Lecture 11. Detection and Segmentation
44. Lecture 10. Recurrent Neural Networks
45. Lecture 9. CNN Architectures
46. Lecture 8. Deep Learning Hardware and Software
47. Lecture 7. Training Neural Networks, part 2
48. Lecture 6. Training Neural Networks, part I
49. Lecture 5. Convolutional Neural Networks
50. Lecture 4. Introduction to Neural Networks
51. Lecture 3. Loss Functions and Optimization
52. Lecture 2. Image Classification & K-nearest neighbor
53. Lecture 1. Computer vision overview & Historical context
54. S_Dbw 聚类评估指标(代码全解析)
55. 数据科学入门之我谈 (2018)
56. $LaTeX$ 常用的数学符号收集与字体整理
57. 一段关于神经网络的故事
58. 为啥一定用残差图检查你的回归分析?
59. ''' Buffer function li
60. All Statistical tests: h
61. 2022.0112 GW next - Hema
62. Python numpy.hanning() 使
63. Kalman filtering 深度解读:卡尔
64. For linux https://blog.c
65. https://baijiahao.baidu.
66. ChatGPT ChatGPT 中文指南: ht
67. 浅析 Hinton 最近提出的 Capsule
68. Python里精确地四舍五入,以及你为什么需要少
69. https://realpython.com/p
70. A list of awesome resour
71. https://baike.baidu.com/
72. 改写为 python3,并且写成一个新的全新的
73. https://www.researchgate
74. http://rlchina.org/ ‘Uns
75. Mahalanobis Distance – U
76. http://www.phys.ufl.edu/
77. https://uvadlc-notebooks
78. https://arxiv.org/pdf/19
79. 1906.02691
80. The Multivariate normal
81. Overview and Installatio
82. https://blog.csdn.net/mi
83. Using machine learning t
84. https://realpython.com/p
85. https://wiseodd.github.i
86. https://www.cnblogs.com/
87. PESummary is a python pa
88. singularity容器使用心得 https:
89. Testing the no-hair theo
90. https://pythonhosted.org
91. For a complete list of a
92. https://makeabilitylab.g
93. https://textbooks.math.g
94. https://docs.scipy.org/d
95. How about that Bayes: Ba
96. A guide for using the Wa
97. Hierarchical Bayesian mo
98. ICA
99. A Conceptual Introductio
更新于 57 分钟前

近期历史最近 100 条记录

2023-07-27 https://textbooks.math.g
2023-05-30 Prompt-Tuning: 深度解读一种新的微调范式
2023-05-30 面向开发者的 ChatGPT 提示工程
2023-05-30 A guide for using the Wa
2023-02-23 ChatGPT ChatGPT 中文指南: ht
2022-12-15 IAIFI Summer School & Workshop
2022-12-15 https://baijiahao.baidu.
2022-12-15 Overview and Installatio
2022-12-15 https://www.cnblogs.com/
2022-12-15 PESummary is a python pa
2022-12-15 singularity容器使用心得 https:
2022-12-15 https://pythonhosted.org
2022-03-06 Mahalanobis Distance – U
2022-03-06 2022.0112 GW next - Hema
2022-03-06 http://rlchina.org/ ‘Uns
2022-03-06 Using machine learning t
2022-03-06 https://makeabilitylab.g
2022-03-06 How about that Bayes: Ba
2022-02-13 http://www.phys.ufl.edu/
2022-02-13 https://blog.csdn.net/mi
2022-02-13 https://docs.scipy.org/d
2021-09-29 A Conceptual Introductio
2021-09-29 https://realpython.com/p
2021-08-28 Git: submodule 子模块简明教程
2021-08-28 https://www.researchgate
2021-08-17 GitHub 不再支持密码验证,如何在 macOS 上实现 Token 登陆配置
2021-08-07 All Statistical tests: h
2021-08-07 Hierarchical Bayesian mo
2021-08-07 https://uvadlc-notebooks
2021-08-03 https://wiseodd.github.i
2021-08-03 浅析 Hinton 最近提出的 Capsule
2021-06-07 https://baike.baidu.com/
2021-05-12 The Multivariate normal
2021-05-12 1906.02691
2021-05-04 For a complete list of a
2021-05-04 Testing the no-hair theo
2021-04-28 解决 GitHub 的 host 域名被限制的问题
2021-04-10 [Paper Summary] Complete Parameter Inference for GW150914 Using Deep Learning
2021-04-09 [Paper Summary] Complete parameter inference for GW150914 using deep learning
2021-04-06 A list of awesome resour
2021-04-04 Particle Swarm Optimization From Scratch Using Python
2021-04-04 Bayes Inference, Bayes Factor, Model Selection
2021-04-04 谱分析 (spectral analysis) 的 SciPy 代码解析
2021-04-04 Python 中负数取余问题
2021-04-04 恒 Q 变换 (Constant-Q transform)
2021-04-04 Unit 3: Structure & Paragraphs(学术写作)
2021-04-04 Python 装饰器之 Property: Setter 和 Getter
2021-04-04 Unit 2: Verbs(学术写作)
2021-04-04 Unit 1: Introduction; principles of effective writing(学术写作)
2021-04-04 S 变换 (Stockwel transform)
2021-04-04 Interactive GW simulation in JavaScript for NSs or BBHs
2021-04-04 Linux/Unix 中 Screen 命令详解
2021-04-04 贝叶斯深度学习前沿进展 (朱军教授)
2021-04-04 深度学习: 从理论到算法 (王力威教授)
2021-04-04 累积引力波事件率图的 python 实现
2021-04-04 Markdown Elements for Hugo/Wowchemy
2021-04-04 傅里叶变换算法及其 python 实现
2021-04-04 Docker 简易入门教程
2021-04-04 Ray Tutorial
2021-04-04 关于感受野 (Receptive field) 你该知道的事
2021-04-04 Centos7/CUDA-9.2/cuDNN-7.3/MXNet-cu92/Floydhub 深度学习环境配置手册
2021-04-04 CS231n课程资料:循环神经网络惊人的有效性
2021-04-04 CS231n课程讲义翻译:神经网络3
2021-04-04 CS231n课程讲义翻译:神经网络2
2021-04-04 CS231n课程讲义翻译:神经网络1
2021-04-04 CS231n课程讲义翻译:卷积神经网络
2021-04-04 CS231n课程讲义翻译:反向传播
2021-04-04 CS231n课程讲义翻译:最优化
2021-04-04 CS231n课程讲义翻译:线性分类
2021-04-04 CS231n课程讲义翻译:图像分类
2021-04-04 Guest Lecture. Adversarial Examples and Adversarial Training
2021-04-04 Guest Lecture. Efficient Methods and Hardware for Deep Learning
2021-04-04 Lecture 14. Deep Reinforcement Learning
2021-04-04 Lecture 13. Visualizing and Understanding
2021-04-04 Lecture 12. Generative Models
2021-04-04 Lecture 11. Detection and Segmentation
2021-04-04 Lecture 10. Recurrent Neural Networks
2021-04-04 Lecture 9. CNN Architectures
2021-04-04 Lecture 8. Deep Learning Hardware and Software
2021-04-04 Lecture 7. Training Neural Networks, part 2
2021-04-04 Lecture 6. Training Neural Networks, part I
2021-04-04 Lecture 5. Convolutional Neural Networks
2021-04-04 Lecture 4. Introduction to Neural Networks
2021-04-04 Lecture 3. Loss Functions and Optimization
2021-04-04 Lecture 2. Image Classification & K-nearest neighbor
2021-04-04 Lecture 1. Computer vision overview & Historical context
2021-04-04 S_Dbw 聚类评估指标(代码全解析)
2021-04-04 数据科学入门之我谈 (2018)
2021-04-04 一段关于神经网络的故事
2021-04-04 为啥一定用残差图检查你的回归分析?
2021-04-04 Python numpy.hanning() 使
2021-04-04 改写为 python3,并且写成一个新的全新的
2021-04-04 Kalman filtering 深度解读:卡尔
2021-04-04 For linux https://blog.c
2021-04-04 https://realpython.com/p
2021-04-04 Python里精确地四舍五入,以及你为什么需要少
2021-04-04 ''' Buffer function li
2021-04-04 https://arxiv.org/pdf/19

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