30 Days of Malware Analysis - What trends can be observed?
cstromblad.com·2d
🦠Malware Analysis
Solving `UK Passport Application` with Haskell
jameshaydon.github.io·4h·
Discuss: Lobsters, Hacker News, r/programming
✅Document Verification
Surrealdb
surrealdb.com·1d·
Discuss: Hacker News
🏠Homelab Archaeology
Statically checking Python dicts for completeness
lukeplant.me.uk·1d
✅Format Verification
Portable Network Graphics (PNG) Specification (Third Edition)
w3.org·4d·
Discuss: Hacker News
🕸️WebP Analysis
A brief introduction to MCP server performance optimization
catchmetrics.io·14h·
Discuss: Hacker News
👁️Observatory Systems
Be Aware of News Mirages
hackernoon.com·14h
📰Content Curation
🌍 Build My Own Telegram Translator Bot with Python
dev.to·1d·
Discuss: DEV
🌀Brotli Internals
A Simple but Accurate Approximation for Multivariate Gaussian Rate-Distortion Function and Its Application in Maximal Coding Rate Reduction
arxiv.org·4d
🧠Neural Compression
nimbme – Nim bare-metal environment
github.com·1d·
Discuss: Hacker News
🎯Emulation Accuracy
🚀 Production-Ready: 6 Advanced Fixes for Your LLMService Class 🚀
dev.to·1d·
Discuss: DEV
💻Local LLMs
Machine Learning Fundamentals: adam optimizer tutorial
dev.to·1d·
Discuss: DEV
📊Feed Optimization
HIDE and Seek: Detecting Hallucinations in Language Models via Decoupled Representations
arxiv.org·4d
👂Psychoacoustic Coding
A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images
arxiv.org·3d
🌀Riemannian Computing
Unlocking Insights Addressing Alcohol Inference Mismatch through Database-Narrative Alignment
arxiv.org·3d
🔗Constraint Handling
Optimal Parameter Design for Power Electronic Converters Using a Probabilistic Learning-Based Stochastic Surrogate Model
arxiv.org·1d
⚙️Tape Engineering
Understanding Political Data as an Asset and Intelligence
exposingtheinvisible.org·17h
📇Dublin Core
Python Fundamentals: attr.s
dev.to·15h·
Discuss: DEV
🌀Brotli Internals
Towards Deeper GCNs: Alleviating Over-smoothing via Iterative Training and Fine-tuning
arxiv.org·4d
📊Learned Metrics
Machine Learning Fundamentals: adam optimizer
dev.to·2d·
Discuss: DEV
📊Quantization