arXiv:2509.17301v1 Announce Type: cross Abstract: In this work, we offer a thorough analytical investigation into the role of shared hyperparameters in a hierarchical Bayesian model, examining their impact on information borrowing and posterior inference. Our approach is rooted in a…
arXiv:2503.09767v2 Announce Type: replace-cross Abstract: Classical unsupervised learning methods like clustering and linear dimensionality reduction parametrize large-scale geometry when it is discrete or linear, while more modern methods from manifold learning find low dimensional representation or infer local geometry by…
arXiv:2509.17385v1 Announce Type: cross Abstract: Inference in semi-supervised (SS) settings has gained substantial attention in recent years due to increased relevance in modern big-data problems. In a typical SS setting, there is a much larger-sized unlabeled data, containing only observations…
arXiv:2504.15325v3 Announce Type: replace-cross Abstract: Agreement measures, such as Cohen’s kappa or intraclass correlation, gauge the matching between two or more classifiers. They are used in a wide range of contexts from medicine, where they evaluate the effectiveness of medical…
arXiv:2509.17752v1 Announce Type: cross Abstract: Tabular data dominates data science but poses challenges for generative models, especially when the data is limited or sensitive. We present a novel approach to generating synthetic tabular data based on the principle of maximum…
arXiv:2505.03432v2 Announce Type: replace-cross Abstract: Score-based Generative Models (SGMs) approximate a data distribution by perturbing it with Gaussian noise and subsequently denoising it via a learned reverse diffusion process. These models excel at modeling complex data distributions and generating diverse…
Parlant is a framework designed to help developers build production-ready AI agents that behave consistently and reliably. A common challenge when deploying large language model (LLM) agents is that they often perform well in testing but fail when interacting with…
From prompt to strategic decision-making: MCP-powered agents for cost-efficient, reliable and sustainable supply chain network design. The post How to Connect an MCP Server for an AI-Powered, Supply-Chain Network Optimization Agent appeared first on Towards Data Science.
Palworld won’t hit 1.0 until next year, but developer Pocketpair is already announcing a farming spinoff: Palworld: Palfarm. Basically, it sounds like the Palworld version of farming simulator games like Stardew Valley. “Each Pal will lend a hand in farm…
