Working for a Vendor with David Gee
blog.ipspace.net·7h
🧲RISC-V Archaeology
Superbase on the Commodore 64
stonetools.ghost.io·1d·
Discuss: Hacker News
🕹️Retro Gaming
Beginner's guide to making AI useful in production
medium.com·3h·
Discuss: Hacker News
⚡Proof Automation
Chip-based phonon splitter brings hybrid quantum networks closer to reality
phys.org·1d
⚛️Quantum Circuits
Adaptive Mesh Refinement for Bandwidth-Efficient Volumetric Video Streaming
dev.to·2d·
Discuss: DEV
📊Rate-Distortion Theory
Automated Microfluidic Sample Prep: AI-Driven Parameter Optimization via Bayesian Reinforcement Learning
dev.to·2d·
Discuss: DEV
🌊Stream Processing
Automated Tourist Route Optimization via Dynamic Constraint Propagation and Multi-Agent Reinforcement Learning
dev.to·12h·
Discuss: DEV
⚡Incremental Computation
Scalable Multi-Modal Knowledge Integration for Robust Anomaly Detection in Industrial Control Systems
dev.to·1d·
Discuss: DEV
🔍Vector Forensics
A New Cartridge for an Old Computer
hackaday.com·9h
🕹️Retro Gaming
StaMo: Unsupervised Learning of Generalizable Robot Motion from Compact State Representation
arxiv.org·10h
🧠Machine Learning
Model Predictive Control-Guided Reinforcement Learning for Implicit Balancing
arxiv.org·10h
✨Effect Handlers
Efficient Test-Time Scaling for Small Vision-Language Models
arxiv.org·10h
🗜️LZW Variants
Decoding the Future: Tensor Networks for Lightning-Fast Wireless Signals
dev.to·2d·
Discuss: DEV
🕸️Tensor Networks
Efficient structure-preserving scheme for chemotaxis PDEs with singular sensitivity in crime and epidemic modeling
arxiv.org·10h
🔗Tailscale
Time-Traveling Data: Seeing Through the Gaps in Time Series Imputation by Arvind Sundararajan
dev.to·4h·
Discuss: DEV
📈Time Series
AI Development Interview Questions : Mock Interviews
dev.to·12h·
Discuss: DEV
🗺️Competency Maps
MuFFIN: Multifaceted Pronunciation Feedback Model with Interactive Hierarchical Neural Modeling
arxiv.org·10h
🗣️CMU Pronouncing
Unlock Peak Model Performance: MINERVA's Surprisingly Simple Feature Selection by Arvind Sundararajan
dev.to·1d·
Discuss: DEV
🧠Machine Learning
Deep Domain Adaptation for Turbofan Engine Remaining Useful Life Prediction: Methodologies, Evaluation and Future Trends
arxiv.org·10h
🧠Machine Learning
Scalable Hyperbolic Embedding Optimization for Geometric Deep Learning on Modular Surfaces
dev.to·1d·
Discuss: DEV
🌀Hyperbolic Geometry