On This Day in Math - June 26
pballew.blogspot.com·1d·
Discuss: www.blogger.com
🗃️Punched Cards
Sci-fi interfaces | IxD Lessons from Sci-Fi
scifiinterfaces.com·3h
🏛Digital humanities
I'm a founder and I wrote an honest review of DocSend alternatives
peony.ink·15h·
Discuss: Hacker News
🏺ZIP Archaeology
Digler: A modular file carving and disk analysis tool in Go (with FUSE mount support)
reddit.com·1d·
Discuss: r/golang
⛏️File Carving
Internationalization-check: Validating your Next.js internationalization
lingual.dev·11h·
Discuss: Hacker News
✅Format Verification
Scientists complete the most thorough analysis yet of India's genetic diversity
phys.org·18h
👪Geneology
Data Types, Data Structures, and Abstract Data Types – What’s the Difference
dev.to·5h·
Discuss: DEV
🧮Algebraic Datatypes
Algorithms for pointwise and piecewise polynomial approximations to the trigonometric functions
arxiv.org·3d
📐Error Bounds
Here is a creative heading for the blog post: "The Phantom Hackers: Unmasking the Invisible Foes of
dev.to·16h·
Discuss: DEV
🛡Cybersecurity
AMF-MedIT: An Efficient Align-Modulation-Fusion Framework for Medical Image-Tabular Data
arxiv.org·2d
🤖Advanced OCR
DBConformer: Dual-Branch Convolutional Transformer for EEG Decoding
arxiv.org·5h
🧠Neural Codecs
Rethinking Oversaturation in Classifier-Free Guidance via Low Frequency
arxiv.org·5h
📊Quantization
Video Perception Models for 3D Scene Synthesis
arxiv.org·1d
📐Projective Geometry
Machine Learning Fundamentals: active learning project
dev.to·1d·
Discuss: DEV
🧠Machine Learning
AI-Driven MRI-based Brain Tumour Segmentation Benchmarking
arxiv.org·5h
🧠Machine Learning
Mastering Multivariate Analysis: A Guide for Data Science Enthusiasts
dev.to·2d·
Discuss: DEV
📊Vector Quantization
LieDetect: Detection of representation orbits of compact Lie groups from point clouds
arxiv.org·3d
🌀Differential Geometry
new2
dev.to·1d·
Discuss: DEV
🧠Query Planners
A Multi-Pass Large Language Model Framework for Precise and Efficient Radiology Report Error Detection
arxiv.org·1d
✅Format Verification
Define-ML: An Approach to Ideate Machine Learning-Enabled Systems
arxiv.org·1d
🧠Machine Learning