The Forest and the Trees
nybooks.com·5h
🌍Cultural Algorithms
LFCS Seminar: Tuesday 28 October: Patrick Totzke
informatics.ed.ac.uk·2d
🔲Cellular Automata
F1 Hungarian GP LIVE: Qualifying start time and schedule as Norris and Piastri fight for pole
the-independent.com·7h
📰SGML
2025: The Year of Intelligence 2.0 ? — 50 Years from the Church Committee to Russiagate Investigation [UPDATE: From TWA 800 to Russiagate: How the FBI Shaped Fa...
inteltoday.org·1d
🔎OSINT Techniques
(1) Fitting hierarchical models in genetics, (2) A Stan model that runs faster with with 400,000 latent parameters, (3) Super-scalable penalized maximum likelih...
statmodeling.stat.columbia.edu·2d
🧮Kolmogorov Complexity
Two Kinds of Do Overs
jefftk.com·2d
⬜Minimalism
Teacher’s fraction grading shocks internet
mindyourdecisions.com·1d
🎯Arithmetic Coding Theory
Mapping the Deep: Marie Tharp’s Physiographic Diagram of the Atlantic Ocean
blogs.loc.gov·2d
🦴Binary Paleography
How to specify backup target when creating recurring backups in Longhorn?
reddit.com·48m·
Discuss: r/kubernetes
📊Differential Backup
If Odin Had Macros
gingerbill.org·1d·
Discuss: Lobsters, Hacker News, r/programming
🦀Rust Macros
LFCS Seminar: Tuesday, 5 August: Michael Sperber
informatics.ed.ac.uk·2d
🧬Functional Programming
IEPG at IETF 123
potaroo.net·2d
📡Network Protocol Design
[D] Math book recommendations for NN theory
reddit.com·3d·
Discuss: r/MachineLearning
💻Programming languages
Novice question if that's ok (using powershell within Golang....)
reddit.com·4h·
Discuss: r/golang
🐚Shell scripting
New Google AI model maps world in 10-meter squares for machines to read
theregister.com·1d·
Discuss: Hacker News
📊Learned Metrics
Physics-Informed Neural Networks for Inverse PDE Problems
towardsdatascience.com·4d
🔗Tailscale
Don't Expose Your IDs: An Introduction to Obfuskey in Python
dev.to·1d·
Discuss: DEV
🧪Binary Fuzzing
Cell-Free Massive MIMO SWIPT with Beyond Diagonal Reconfigurable Intelligent Surfaces
arxiv.org·1d
📡Information theory
First set up
reddit.com·19h·
Discuss: r/homelab
🏠HomeLab
FedCVD++: Communication-Efficient Federated Learning for Cardiovascular Risk Prediction with Parametric and Non-Parametric Model Optimization
arxiv.org·1d
🤐Secure Multiparty