This has really been quite a journey for me lately. And regarding the frequently asked question “Why did you choose Python for Machine Learning?” I guess it is about time to write my script. In this article, I really don’t mean to tell you why you or anyone else should use Python. But read on if you are interested in my opinion.

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In a high school math class, the solution to the equation bx = y is the logarithm of x in base b. The implicit context of the equation is the real numbers, and the solution is easy to calculate. The same problem in the context of finite groups is called the discrete logarithm problem, and it is difficult to solve for large groups. In particular, it is impractical to solve when working modulo a sufficiently large prime number or when working […]

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arXiv:2601.17022v1 Announce Type: new Abstract: Technological developments have produced methods that can generate educational videos from input text or sound. Recently, the use of deep learning techniques for image and video generation has been widely explored, particularly in education. However, generating video content from conditional inputs such as text or speech remains a challenging area. In this paper, we introduce a novel method to the educational structure, Generative Adversarial Network (GAN), which develop frame-for-frame frameworks and are able […]

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Deep learning (DL)-based image reconstruction methods for photoacoustic computed tomography (PACT) have developed rapidly in recent years. However, most existing methods have not employed standardized datasets, and their evaluations rely on traditional image quality (IQ) metrics that may lack clinical relevance. The absence of a standardized framework for clinically meaningful IQ assessment hinders fair comparison and raises concerns about the reproducibility and reliability of reported advancements in PACT. A benchmarking framework is proposed that provides open-source, anatomically plausible […]

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arXiv:2601.17374v1 Announce Type: new Abstract: Data-driven methods for the solution of inverse problems have become widely popular in recent years thanks to the rise of machine learning techniques. A popular approach concerns the training of a generative model on additional data to learn a bespoke prior for the problem at hand. In this article we present an analysis for such problems by presenting quantitative error bounds for minimum Wasserstein-2 generative models for the prior. We show that under […]

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The continuous-review (s,S) inventory model is a cornerstone of stochastic inventory theory, yet its analysis becomes analytically intractable when dealing with non-Markovian systems. In such systems, evaluating long-run performance measures typically relies on costly simulation. This paper proposes a supervised learning framework via a neural network model for approximating stationary performance measures of (s,S) inventory systems with general distributions for the interarrival time between demands and lead times under lost sales. Simulations are first used to generate training […]

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arXiv:2601.12155v1 Announce Type: new Abstract: Reconstructing 3D objects from images is inherently an ill-posed problem due to ambiguities in geometry, appearance, and topology. This paper introduces collaborative inverse rendering with persistent homology priors, a novel strategy that leverages topological constraints to resolve these ambiguities. By incorporating priors that capture critical features such as tunnel loops and handle loops, our approach directly addresses the difficulty of reconstructing high-genus surfaces. The collaboration between photometric consistency from multi-view images and homology-based […]

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Home Table of Contents Building Your First Streamlit App: Uploads, Charts, and Filters (Part 2) Upload Page: Custom CSV Uploads Code Block Line-by-Line Explanation Teaching Points Profile Page: Descriptive Stats and Missingness Code Block Line-by-Line Explanation Why It Matters Visualize Page: Line, Bar, Scatter, and Histogram Code Block Line-by-Line Explanation Design and Performance Notes Filter Page: Interactive Numeric Range Filtering Code Block Line-by-Line Explanation Teaching Notes Export Page: Download Filtered Data as CSV Code Block Line-by-Line Explanation Best […]

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