Why Blogging Is More Than Just Writing Online Read more ›
Covariance matrices used in astronomical and cosmological parameter inference are often estimated from a finite number of simulations, so covariance uncertainty can affect posterior calibration and parameter constraints. We study covariance regularisation from the perspective of likelihood-based inference with simulation-estimated covariance matrices. First, we analyse scalar covariance scaling under the Gaussian plug-in likelihood and the cov... Read more ›
The median micro-SaaS makes $500/mo; ~70% never clear $1K. Here’s how to spot the verified ones — and the years they actually took. Read more ›
What do LLMs make of leading arguments in the Philosophy of Mind? Read more ›
An interactive knowledge graph of the physical and geopolitical constraints that govern the global economy. 393 nodes, 562 sourced mechanism edges, 17 feedback loops — every link in plain language, graded and cited. Find where problems cascade, and where to profit. Read more ›
By Pyrrhonian Skepticism about Philosophy (PSP) we mean the view that, considering the permanent and pervasive dissensus in philosophy, you cannot maintain your philosophical beliefs—you should suspend them, or at least significantly (and perhaps painfully) reduce your confidence in their... Read More › Source Read more ›
Author(s): Klaus Zollner, Lukas Cvitkovich, Riccardo Silvioli, Andreas V. Stier, and Jaroslav FabianMagnetic proximity effects in $\text{Co}\text{/}\text{hBN}\text{/}\text{graphene}$ heterostructures are systematically analyzed via first-principles calculations, demonstrating a pronounced localized spatial variation of the induced spin polarization of graphene's Dirac states. The proximity-induced…[Phys. Rev. B 113, 235142] Published Tue Jun 23, 2026 Read more ›
As a staff engineer who has spent more than 15 years building and scaling production systems, I have noticed the basic CRUD mental model… Read more ›
to get full episodes, full archive, and join the Discord community. The Transmitter is an online publication that aims to deliver useful information, insights and tools to build bridges across neuroscience and advance research. Visit thetransmitter.org to explore the latest neuroscience news and perspectives, written by journalists and scientists. Read more about . Sign up for to be notified every time a new Brain Inspired episode is released. To explore more neuroscience news and perspective... Read more ›
From Bayes’ Theorem to Maximum Likelihood — The Mathematics of Uncertainty Read more ›
2026-06-22 19:22:39.944184+02 by 0 comments Read more ›
The math lesson I didn’t know I needed Read more ›
Before the past year, many of us took computer memory for granted. It was one of the lower-cost parts of a PC build and was usually available in whatever quantity one desired. As its cost has skyro… Read more ›
A guide to tailoring topologies, feedback loops, and quality gates for self-optimizing workflows Read more ›
A new library of combinatorial optimization problems provides a standardized testing ground to rigorously compare quantum and classical algorithms, paving the way for demonstrating quantum utility. Read more ›
Notion-style personal site. Stack: NextJS, Convex, BlockNote, Cloudflare R2 - terryds/notion-style-personal-site Read more ›
Epistemic status: I feel reasonably confident (~75%) that some form of this is a worthwhile project. Looking for feedback to reduce that uncertainty.“Hedonium” is a theoretical, minimally conscious substance optimized for experiencing happiness. Imagine a mind pared down to the bare essentials required for having happy experiences, instantiated as cheaply as possible.Nobody has built hedonium yet. Nobody has tried to build hedonium yet. Nobody has even laid out the blueprint for how you would... Read more ›
Xbox's Obsidian Entertainment, the dev behind The Outer Worlds 2, Avowed, and others, is being sued for "pattern of wage and hour violations." Read more ›
AbstractMotivationHigh-dimensional omics data are typically measured on limited sample sizes, which challenges model-based clustering methods such as Gaussian mixture models (GMMs), often leading to instability and poor generalization under complex mixture structures. To address these limitations, we developed Praxis-BGM, a natural-gradient variational inference framework for GMMs. Praxis-BGM enables semi-supervised transfer learning by incorporating an informative prior GMM estimated from la... Read more ›