LeakIX - Host veryunknown.com

Domain veryunknown.com

United States

GOOGLE-CLOUD-PLATFORM

MacOS file listing through .DS_Store file

.DS_Store” is an abbreviation for “Desktop Services Store”. These files are created automatically by Apples “Finder” software (which is part of their OS).

They store information about the files within a folder, including display options of folders, such as icon positions and view settings.

It may happen that .DS_Store files inadvertently leak filenames such as database backups or private administration panels.

IP: 35.185.44.232
Domain: www.veryunknown.com
Port: 443
URL: https://www.veryunknown.com

First seen 2022-10-25 03:11
Last seen 2026-01-02 10:25
Open for 1165 days
- Severity: low
  Fingerprint: 5f32cf5d6962f09c63442d9d63442d9d8bc298658bc298658bc298658bc29865
```
Found 1 files trough .DS_Store spidering:

/css
```
  Found on 2026-01-02 10:25
- Severity: low
  Fingerprint: 5f32cf5d6962f09c7cf176427cf176422b63f4825bdb4d635bdb4d635bdb4d63
```
Found 2 files trough .DS_Store spidering:

/css
/images
```
  Found on 2022-10-25 03:11
Create report
MacOS file listing through .DS_Store file

.DS_Store” is an abbreviation for “Desktop Services Store”. These files are created automatically by Apples “Finder” software (which is part of their OS).

They store information about the files within a folder, including display options of folders, such as icon positions and view settings.

It may happen that .DS_Store files inadvertently leak filenames such as database backups or private administration panels.

IP: 35.185.44.232
Domain: veryunknown.com
Port: 443
URL: https://veryunknown.com

First seen 2022-10-25 02:53
Last seen 2026-01-02 05:19
Open for 1165 days
- Severity: low
  Fingerprint: 5f32cf5d6962f09c63442d9d63442d9d8bc298658bc298658bc298658bc29865
```
Found 1 files trough .DS_Store spidering:

/css
```
  Found on 2026-01-02 05:19
- Severity: low
  Fingerprint: 5f32cf5d6962f09c7cf176427cf176422b63f4825bdb4d635bdb4d635bdb4d63
```
Found 2 files trough .DS_Store spidering:

/css
/images
```
  Found on 2022-10-25 02:53
Create report

Open service 35.185.44.232:443 · veryunknown.com

2026-01-09 05:18

HTTP/1.1 200 OK
Cache-Control: max-age=600
Content-Length: 9480
Content-Type: text/html; charset=utf-8
Etag: "58d5695a6579d87aba87e8122861e2d657e637faf2ea4e8998acca7f4fdd20ce"
Expires: Fri, 09 Jan 2026 05:28:16 UTC
Last-Modified: Sat, 10 May 2025 06:12:13 GMT
Permissions-Policy: interest-cohort=()
Vary: Origin
X-Request-Id: 01KEGK1V1HVS7JFVW9G7MSW3JK
Date: Fri, 09 Jan 2026 05:18:16 GMT
Connection: close

Page title: VeryUnknown

<!DOCTYPE html>
<html lang="en"><meta charset="utf-8" />

  <title>VeryUnknown</title>


<meta name="author" content="VeryUnknown"/>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
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<header>
  <nav class="navbar">
  <div class="nav">
    

    <ul class="nav-links">
      
    </ul>
  </div>
</nav>
  <div class="intro-header">
    <div class="container">
      <div class="page-heading">
        
          <h1>VeryUnknown</h1>
          
            <div class="abstract">
              <p>
                Casual essays on physics, mathematics and computing<br>
                <a class="eml" href="#">[enable JavaScript to see contact information]</a>
              </p>
            </div>
          
        
      </div>
    </div>
  </div>
</header>

<div id="content">
<div class="container" role="main">
    <div class="posts-list">
      
        
      

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/generative-ai/" class="post-read-more">Understanding Generative AI (Stable Diffusion) as Galton Board</a></h5>
  <div class="post-entry">
	Generative AI can be magical, but the mathematical ideas and intuition underlying the popular &#39;Stable Diffusion&#39; approach can be opaque and somewhat inaccessible. However, these ideas are interesting so we will approach the topic in a distilled manner - understanding it as a &#39;Galton Board&#39;, which will not demand any prior mathematical or AI background.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/foundations-ppo/" class="post-read-more">Mathematical foundations of PPO and TRPO</a></h5>
  <div class="post-entry">
	Reinforcement learning is an important tool in the Machine Learning toolbox. It has been used to teach computers how to play the game of Go or to enable resonating capabilities in large language models. A popular reinforcement learning algorithm is the Policy Optimization Optimization (PPO) algorithm. We will discuss the mathematical motivation behind it in detail, especially the derivation of the notion of trust region as introduced in the Trust Region Policy Optimization algorithm. Familiarity with reinforcement learning and linear algebra will be assumed.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/penrose-graphical-notation/" class="post-read-more">Penrose Graphical Notation</a></h5>
  <div class="post-entry">
	Mathematics is usually written using symbols, however, these symbols are not magic, but purposeful inventions. Is there an interesting and useful example of non-symbol-based mathematical notation? There is and we will do an introduction to Roger Penrose&#39;s (physics Nobel Laureate) graphical notation, which we will apply to a classical physics problem. Familiarity with vector calculus will be assumed.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/p

Found 2026-01-09 by HttpPlugin

Create report

Open service 35.185.44.232:443 · www.veryunknown.com

2026-01-09 03:20

HTTP/1.1 200 OK
Cache-Control: max-age=600
Content-Length: 9480
Content-Type: text/html; charset=utf-8
Etag: "58d5695a6579d87aba87e8122861e2d657e637faf2ea4e8998acca7f4fdd20ce"
Expires: Fri, 09 Jan 2026 03:30:07 UTC
Last-Modified: Sat, 10 May 2025 06:12:13 GMT
Permissions-Policy: interest-cohort=()
Vary: Origin
X-Request-Id: 01KEGC9FXACRX9D0SJ7M809W6Z
Date: Fri, 09 Jan 2026 03:20:07 GMT
Connection: close

Page title: VeryUnknown

<!DOCTYPE html>
<html lang="en"><meta charset="utf-8" />

  <title>VeryUnknown</title>


<meta name="author" content="VeryUnknown"/>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<link rel="stylesheet" href="https://veryunknown.com/css/latex.css" />
<link rel="stylesheet" href="https://veryunknown.com/css/main.css" />
<script src="https://veryunknown.com/js/email.js" defer></script>

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          function gtag(){dataLayer.push(arguments);}
          gtag('js', new Date());
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<header>
  <nav class="navbar">
  <div class="nav">
    

    <ul class="nav-links">
      
    </ul>
  </div>
</nav>
  <div class="intro-header">
    <div class="container">
      <div class="page-heading">
        
          <h1>VeryUnknown</h1>
          
            <div class="abstract">
              <p>
                Casual essays on physics, mathematics and computing<br>
                <a class="eml" href="#">[enable JavaScript to see contact information]</a>
              </p>
            </div>
          
        
      </div>
    </div>
  </div>
</header>

<div id="content">
<div class="container" role="main">
    <div class="posts-list">
      
        
      

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/generative-ai/" class="post-read-more">Understanding Generative AI (Stable Diffusion) as Galton Board</a></h5>
  <div class="post-entry">
	Generative AI can be magical, but the mathematical ideas and intuition underlying the popular &#39;Stable Diffusion&#39; approach can be opaque and somewhat inaccessible. However, these ideas are interesting so we will approach the topic in a distilled manner - understanding it as a &#39;Galton Board&#39;, which will not demand any prior mathematical or AI background.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/foundations-ppo/" class="post-read-more">Mathematical foundations of PPO and TRPO</a></h5>
  <div class="post-entry">
	Reinforcement learning is an important tool in the Machine Learning toolbox. It has been used to teach computers how to play the game of Go or to enable resonating capabilities in large language models. A popular reinforcement learning algorithm is the Policy Optimization Optimization (PPO) algorithm. We will discuss the mathematical motivation behind it in detail, especially the derivation of the notion of trust region as introduced in the Trust Region Policy Optimization algorithm. Familiarity with reinforcement learning and linear algebra will be assumed.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/penrose-graphical-notation/" class="post-read-more">Penrose Graphical Notation</a></h5>
  <div class="post-entry">
	Mathematics is usually written using symbols, however, these symbols are not magic, but purposeful inventions. Is there an interesting and useful example of non-symbol-based mathematical notation? There is and we will do an introduction to Roger Penrose&#39;s (physics Nobel Laureate) graphical notation, which we will apply to a classical physics problem. Familiarity with vector calculus will be assumed.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/p

Found 2026-01-09 by HttpPlugin

Create report

Open service 35.185.44.232:443 · www.veryunknown.com

2026-01-02 10:25

HTTP/1.1 200 OK
Cache-Control: max-age=600
Content-Length: 9480
Content-Type: text/html; charset=utf-8
Etag: "58d5695a6579d87aba87e8122861e2d657e637faf2ea4e8998acca7f4fdd20ce"
Expires: Fri, 02 Jan 2026 10:35:50 UTC
Last-Modified: Sat, 10 May 2025 06:12:13 GMT
Permissions-Policy: interest-cohort=()
Vary: Origin
X-Request-Id: 01KDZ3VZ58Z8X4QGZVS2AHFF18
Date: Fri, 02 Jan 2026 10:25:50 GMT
Connection: close

Page title: VeryUnknown

<!DOCTYPE html>
<html lang="en"><meta charset="utf-8" />

  <title>VeryUnknown</title>


<meta name="author" content="VeryUnknown"/>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
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          function gtag(){dataLayer.push(arguments);}
          gtag('js', new Date());
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<header>
  <nav class="navbar">
  <div class="nav">
    

    <ul class="nav-links">
      
    </ul>
  </div>
</nav>
  <div class="intro-header">
    <div class="container">
      <div class="page-heading">
        
          <h1>VeryUnknown</h1>
          
            <div class="abstract">
              <p>
                Casual essays on physics, mathematics and computing<br>
                <a class="eml" href="#">[enable JavaScript to see contact information]</a>
              </p>
            </div>
          
        
      </div>
    </div>
  </div>
</header>

<div id="content">
<div class="container" role="main">
    <div class="posts-list">
      
        
      

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/generative-ai/" class="post-read-more">Understanding Generative AI (Stable Diffusion) as Galton Board</a></h5>
  <div class="post-entry">
	Generative AI can be magical, but the mathematical ideas and intuition underlying the popular &#39;Stable Diffusion&#39; approach can be opaque and somewhat inaccessible. However, these ideas are interesting so we will approach the topic in a distilled manner - understanding it as a &#39;Galton Board&#39;, which will not demand any prior mathematical or AI background.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/foundations-ppo/" class="post-read-more">Mathematical foundations of PPO and TRPO</a></h5>
  <div class="post-entry">
	Reinforcement learning is an important tool in the Machine Learning toolbox. It has been used to teach computers how to play the game of Go or to enable resonating capabilities in large language models. A popular reinforcement learning algorithm is the Policy Optimization Optimization (PPO) algorithm. We will discuss the mathematical motivation behind it in detail, especially the derivation of the notion of trust region as introduced in the Trust Region Policy Optimization algorithm. Familiarity with reinforcement learning and linear algebra will be assumed.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/penrose-graphical-notation/" class="post-read-more">Penrose Graphical Notation</a></h5>
  <div class="post-entry">
	Mathematics is usually written using symbols, however, these symbols are not magic, but purposeful inventions. Is there an interesting and useful example of non-symbol-based mathematical notation? There is and we will do an introduction to Roger Penrose&#39;s (physics Nobel Laureate) graphical notation, which we will apply to a classical physics problem. Familiarity with vector calculus will be assumed.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/p

Found 2026-01-02 by HttpPlugin

Create report

Open service 35.185.44.232:443 · veryunknown.com

2026-01-02 05:19

HTTP/1.1 200 OK
Cache-Control: max-age=600
Content-Length: 9480
Content-Type: text/html; charset=utf-8
Etag: "58d5695a6579d87aba87e8122861e2d657e637faf2ea4e8998acca7f4fdd20ce"
Expires: Fri, 02 Jan 2026 05:29:20 UTC
Last-Modified: Sat, 10 May 2025 06:12:13 GMT
Permissions-Policy: interest-cohort=()
Vary: Origin
X-Request-Id: 01KDYJARB2QVTQ6Y0S87KCKTXE
Date: Fri, 02 Jan 2026 05:19:20 GMT
Connection: close

Page title: VeryUnknown

<!DOCTYPE html>
<html lang="en"><meta charset="utf-8" />

  <title>VeryUnknown</title>


<meta name="author" content="VeryUnknown"/>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<link rel="stylesheet" href="https://veryunknown.com/css/latex.css" />
<link rel="stylesheet" href="https://veryunknown.com/css/main.css" />
<script src="https://veryunknown.com/js/email.js" defer></script>

<script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
<meta name="generator" content="Hugo 0.140.2"><body>

  




    
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          function gtag(){dataLayer.push(arguments);}
          gtag('js', new Date());
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<header>
  <nav class="navbar">
  <div class="nav">
    

    <ul class="nav-links">
      
    </ul>
  </div>
</nav>
  <div class="intro-header">
    <div class="container">
      <div class="page-heading">
        
          <h1>VeryUnknown</h1>
          
            <div class="abstract">
              <p>
                Casual essays on physics, mathematics and computing<br>
                <a class="eml" href="#">[enable JavaScript to see contact information]</a>
              </p>
            </div>
          
        
      </div>
    </div>
  </div>
</header>

<div id="content">
<div class="container" role="main">
    <div class="posts-list">
      
        
      

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/generative-ai/" class="post-read-more">Understanding Generative AI (Stable Diffusion) as Galton Board</a></h5>
  <div class="post-entry">
	Generative AI can be magical, but the mathematical ideas and intuition underlying the popular &#39;Stable Diffusion&#39; approach can be opaque and somewhat inaccessible. However, these ideas are interesting so we will approach the topic in a distilled manner - understanding it as a &#39;Galton Board&#39;, which will not demand any prior mathematical or AI background.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/foundations-ppo/" class="post-read-more">Mathematical foundations of PPO and TRPO</a></h5>
  <div class="post-entry">
	Reinforcement learning is an important tool in the Machine Learning toolbox. It has been used to teach computers how to play the game of Go or to enable resonating capabilities in large language models. A popular reinforcement learning algorithm is the Policy Optimization Optimization (PPO) algorithm. We will discuss the mathematical motivation behind it in detail, especially the derivation of the notion of trust region as introduced in the Trust Region Policy Optimization algorithm. Familiarity with reinforcement learning and linear algebra will be assumed.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/penrose-graphical-notation/" class="post-read-more">Penrose Graphical Notation</a></h5>
  <div class="post-entry">
	Mathematics is usually written using symbols, however, these symbols are not magic, but purposeful inventions. Is there an interesting and useful example of non-symbol-based mathematical notation? There is and we will do an introduction to Roger Penrose&#39;s (physics Nobel Laureate) graphical notation, which we will apply to a classical physics problem. Familiarity with vector calculus will be assumed.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/p

Found 2026-01-02 by HttpPlugin

Create report

Open service 35.185.44.232:443 · www.veryunknown.com

2025-12-22 19:20

HTTP/1.1 200 OK
Cache-Control: max-age=600
Content-Length: 9480
Content-Type: text/html; charset=utf-8
Etag: "58d5695a6579d87aba87e8122861e2d657e637faf2ea4e8998acca7f4fdd20ce"
Expires: Mon, 22 Dec 2025 19:30:55 UTC
Last-Modified: Sat, 10 May 2025 06:12:13 GMT
Permissions-Policy: interest-cohort=()
Vary: Origin
X-Request-Id: 01KD3R3TASEESVCECT59JEA03M
Date: Mon, 22 Dec 2025 19:20:55 GMT
Connection: close

Page title: VeryUnknown

<!DOCTYPE html>
<html lang="en"><meta charset="utf-8" />

  <title>VeryUnknown</title>


<meta name="author" content="VeryUnknown"/>
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<link rel="stylesheet" href="https://veryunknown.com/css/latex.css" />
<link rel="stylesheet" href="https://veryunknown.com/css/main.css" />
<script src="https://veryunknown.com/js/email.js" defer></script>

<script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js"></script>
<meta name="generator" content="Hugo 0.140.2"><body>

  




    
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<header>
  <nav class="navbar">
  <div class="nav">
    

    <ul class="nav-links">
      
    </ul>
  </div>
</nav>
  <div class="intro-header">
    <div class="container">
      <div class="page-heading">
        
          <h1>VeryUnknown</h1>
          
            <div class="abstract">
              <p>
                Casual essays on physics, mathematics and computing<br>
                <a class="eml" href="#">[enable JavaScript to see contact information]</a>
              </p>
            </div>
          
        
      </div>
    </div>
  </div>
</header>

<div id="content">
<div class="container" role="main">
    <div class="posts-list">
      
        
      

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/generative-ai/" class="post-read-more">Understanding Generative AI (Stable Diffusion) as Galton Board</a></h5>
  <div class="post-entry">
	Generative AI can be magical, but the mathematical ideas and intuition underlying the popular &#39;Stable Diffusion&#39; approach can be opaque and somewhat inaccessible. However, these ideas are interesting so we will approach the topic in a distilled manner - understanding it as a &#39;Galton Board&#39;, which will not demand any prior mathematical or AI background.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/foundations-ppo/" class="post-read-more">Mathematical foundations of PPO and TRPO</a></h5>
  <div class="post-entry">
	Reinforcement learning is an important tool in the Machine Learning toolbox. It has been used to teach computers how to play the game of Go or to enable resonating capabilities in large language models. A popular reinforcement learning algorithm is the Policy Optimization Optimization (PPO) algorithm. We will discuss the mathematical motivation behind it in detail, especially the derivation of the notion of trust region as introduced in the Trust Region Policy Optimization algorithm. Familiarity with reinforcement learning and linear algebra will be assumed.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/penrose-graphical-notation/" class="post-read-more">Penrose Graphical Notation</a></h5>
  <div class="post-entry">
	Mathematics is usually written using symbols, however, these symbols are not magic, but purposeful inventions. Is there an interesting and useful example of non-symbol-based mathematical notation? There is and we will do an introduction to Roger Penrose&#39;s (physics Nobel Laureate) graphical notation, which we will apply to a classical physics problem. Familiarity with vector calculus will be assumed.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/p

Found 2025-12-22 by HttpPlugin

Create report

Open service 35.185.44.232:443 · veryunknown.com

2025-12-22 07:50

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          <h1>VeryUnknown</h1>
          
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                Casual essays on physics, mathematics and computing<br>
                <a class="eml" href="#">[enable JavaScript to see contact information]</a>
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<h5 class="post-title"><a href="https://veryunknown.com/post/generative-ai/" class="post-read-more">Understanding Generative AI (Stable Diffusion) as Galton Board</a></h5>
  <div class="post-entry">
	Generative AI can be magical, but the mathematical ideas and intuition underlying the popular &#39;Stable Diffusion&#39; approach can be opaque and somewhat inaccessible. However, these ideas are interesting so we will approach the topic in a distilled manner - understanding it as a &#39;Galton Board&#39;, which will not demand any prior mathematical or AI background.
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<h5 class="post-title"><a href="https://veryunknown.com/post/foundations-ppo/" class="post-read-more">Mathematical foundations of PPO and TRPO</a></h5>
  <div class="post-entry">
	Reinforcement learning is an important tool in the Machine Learning toolbox. It has been used to teach computers how to play the game of Go or to enable resonating capabilities in large language models. A popular reinforcement learning algorithm is the Policy Optimization Optimization (PPO) algorithm. We will discuss the mathematical motivation behind it in detail, especially the derivation of the notion of trust region as introduced in the Trust Region Policy Optimization algorithm. Familiarity with reinforcement learning and linear algebra will be assumed.
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<h5 class="post-title"><a href="https://veryunknown.com/post/penrose-graphical-notation/" class="post-read-more">Penrose Graphical Notation</a></h5>
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	Mathematics is usually written using symbols, however, these symbols are not magic, but purposeful inventions. Is there an interesting and useful example of non-symbol-based mathematical notation? There is and we will do an introduction to Roger Penrose&#39;s (physics Nobel Laureate) graphical notation, which we will apply to a classical physics problem. Familiarity with vector calculus will be assumed.
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          <h1>VeryUnknown</h1>
          
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                Casual essays on physics, mathematics and computing<br>
                <a class="eml" href="#">[enable JavaScript to see contact information]</a>
              </p>
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<h5 class="post-title"><a href="https://veryunknown.com/post/generative-ai/" class="post-read-more">Understanding Generative AI (Stable Diffusion) as Galton Board</a></h5>
  <div class="post-entry">
	Generative AI can be magical, but the mathematical ideas and intuition underlying the popular &#39;Stable Diffusion&#39; approach can be opaque and somewhat inaccessible. However, these ideas are interesting so we will approach the topic in a distilled manner - understanding it as a &#39;Galton Board&#39;, which will not demand any prior mathematical or AI background.
  </div>
</article>

      
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<h5 class="post-title"><a href="https://veryunknown.com/post/foundations-ppo/" class="post-read-more">Mathematical foundations of PPO and TRPO</a></h5>
  <div class="post-entry">
	Reinforcement learning is an important tool in the Machine Learning toolbox. It has been used to teach computers how to play the game of Go or to enable resonating capabilities in large language models. A popular reinforcement learning algorithm is the Policy Optimization Optimization (PPO) algorithm. We will discuss the mathematical motivation behind it in detail, especially the derivation of the notion of trust region as introduced in the Trust Region Policy Optimization algorithm. Familiarity with reinforcement learning and linear algebra will be assumed.
  </div>
</article>

      
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<h5 class="post-title"><a href="https://veryunknown.com/post/penrose-graphical-notation/" class="post-read-more">Penrose Graphical Notation</a></h5>
  <div class="post-entry">
	Mathematics is usually written using symbols, however, these symbols are not magic, but purposeful inventions. Is there an interesting and useful example of non-symbol-based mathematical notation? There is and we will do an introduction to Roger Penrose&#39;s (physics Nobel Laureate) graphical notation, which we will apply to a classical physics problem. Familiarity with vector calculus will be assumed.
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          <h1>VeryUnknown</h1>
          
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                Casual essays on physics, mathematics and computing<br>
                <a class="eml" href="#">[enable JavaScript to see contact information]</a>
              </p>
            </div>
          
        
      </div>
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        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/generative-ai/" class="post-read-more">Understanding Generative AI (Stable Diffusion) as Galton Board</a></h5>
  <div class="post-entry">
	Generative AI can be magical, but the mathematical ideas and intuition underlying the popular &#39;Stable Diffusion&#39; approach can be opaque and somewhat inaccessible. However, these ideas are interesting so we will approach the topic in a distilled manner - understanding it as a &#39;Galton Board&#39;, which will not demand any prior mathematical or AI background.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/foundations-ppo/" class="post-read-more">Mathematical foundations of PPO and TRPO</a></h5>
  <div class="post-entry">
	Reinforcement learning is an important tool in the Machine Learning toolbox. It has been used to teach computers how to play the game of Go or to enable resonating capabilities in large language models. A popular reinforcement learning algorithm is the Policy Optimization Optimization (PPO) algorithm. We will discuss the mathematical motivation behind it in detail, especially the derivation of the notion of trust region as introduced in the Trust Region Policy Optimization algorithm. Familiarity with reinforcement learning and linear algebra will be assumed.
  </div>
</article>

      
        <article class="post-preview">
<h5 class="post-title"><a href="https://veryunknown.com/post/penrose-graphical-notation/" class="post-read-more">Penrose Graphical Notation</a></h5>
  <div class="post-entry">
	Mathematics is usually written using symbols, however, these symbols are not magic, but purposeful inventions. Is there an interesting and useful example of non-symbol-based mathematical notation? There is and we will do an introduction to Roger Penrose&#39;s (physics Nobel Laureate) graphical notation, which we will apply to a classical physics problem. Familiarity with vector calculus will be assumed.
  </div>
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