🎯 Number Wheels: The Simple Tool That Makes Number Sense Click
guidedmath.wordpress.com·5h
📐Interval Arithmetic
A new information-theory framework reveals when multi-agent AI systems truly work as a team
the-decoder.com·14h
🔲Cellular Automata
Padding
reddit.com·19h·
Discuss: r/golang
🔧KAITAI
I built a translator for spatial thinking (because I can't interview in Python)
graemefawcett.ca·1d·
Discuss: Hacker News
🔗Concatenative Programming
Seeing the Future: Mastering Action Recognition with Recurrence-Complete Architectures
dev.to·2d·
Discuss: DEV
🌊Streaming Algorithms
CIR-CoT: Towards Interpretable Composed Image Retrieval via End-to-End Chain-of-Thought Reasoning
arxiv.org·1d
🧮Vector Embeddings
A Total Variation Regularized Framework for Epilepsy-Related MRI Image Segmentation
arxiv.org·2d
📊Learned Metrics
Automated Spectral Analysis for Precision Dimension Stone Grading & Yield Optimization
dev.to·12h·
Discuss: DEV
🌈Spectroscopy
The Library Method: Understanding @cache
dev.to·1d·
Discuss: DEV
⚡Cache Theory
VideoNorms: Benchmarking Cultural Awareness of Video Language Models
arxiv.org·1d
📊Learned Metrics
ACE: Attribution-Controlled Knowledge Editing for Multi-hop Factual Recall
arxiv.org·1d
✨Effect Handlers
Automated Fault Prediction and Residual Lifetime Estimation in Cryogenic Pumps via Dynamic Bayesian Network (DBN)
dev.to·9h·
Discuss: DEV
📊Quantization
ParsTranslit: Truly Versatile Tajik-Farsi Transliteration
arxiv.org·1d
📜Digital Philology
Data-Error Scaling Laws in Machine Learning on Combinatorial Mutation-prone Sets: Proteins and Small Molecules
arxiv.org·1d
🧮Kolmogorov Complexity
Synergy Between the Strong and the Weak: Spiking Neural Networks are Inherently Self-Distillers
arxiv.org·1d
🧠Machine Learning
Recurrent Natural Policy Gradient for POMDPs
arxiv.org·1d
🔲Cellular Automata
Enhanced Parasitic R/L Extraction in Die-Stacked ICs via Adaptive Finite Element Modeling and Bayesian Optimization
dev.to·1h·
Discuss: DEV
⚡Circuit Archaeology
[R] DeepSeek 3.2's sparse attention mechanism
reddit.com·1d·
Discuss: r/MachineLearning
🌀Brotli Internals
GNN Blind Spots: The Hidden Cost of Powerful Graph Models
dev.to·21h·
Discuss: DEV
🕸️Graph Embeddings
Out-of-Distribution Generalization in Climate-Aware Yield Prediction with Earth Observation Data
arxiv.org·1d
🧠Machine Learning