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Cyberpower begins selling desktop PCs with carbon nanotube CPU cooling
pcgamer.com·1h·
Discuss: Hacker News
Extend ActiveStorage for Ruby on Rails with Custom Previewers
blog.appsignal.com·1d·
Discuss: Hacker News
Why Metropolis–Hastings Works
gregorygundersen.com·2d·
Discuss: Lobsters, Hacker News
📐Computational geometry
Rendering 120k+ Entities
mobcitygame.com·3d·
Discuss: Hacker News
🧩Procedural Generation
original ↗
nickyreinert.de·2d·
Discuss: Hacker News
🧩Procedural Generation
I chose OCaml as my primary language
xvw.lol·19h·
Discuss: Lobsters, Hacker News, r/programming
A Parametric Bi-Directional Curvature-Based Framework for Image Artifact Classification and Quantification
arxiv.org·1d
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Spatial-ORMLLM: Improve Spatial Relation Understanding in the Operating Room with Multimodal Large Language Model
arxiv.org·2d
📐Computational geometry
Decoding Neural Emotion Patterns through Natural Language Processing Embeddings
arxiv.org·9h
Exploring the Challenges and Opportunities of AI-assisted Codebase Generation
arxiv.org·2d
🧩Procedural Generation
MoSSDA: A Semi-Supervised Domain Adaptation Framework for Multivariate Time-Series Classification using Momentum Encoder
arxiv.org·1d
Understanding Transformers through the Lens of Pavlovian Conditioning
arxiv.org·1d
Long-Term Client Selection for Federated Learning with Non-IID Data: A Truthful Auction Approach
arxiv.org·9h
Sparse Variational Student-t Processes
arxiv.org·2d
🧩Procedural Generation
Comparative study of machine learning and statistical methods for automatic identification and quantification in {\gamma}-ray spectrometry
arxiv.org·1d
Autonomous Air-Ground Vehicle Operations Optimization in Hazardous Environments: A Multi-Armed Bandit Approach
arxiv.org·2d
🧩Procedural Generation
LET-US: Long Event-Text Understanding of Scenes
arxiv.org·2d
🧩Procedural Generation
Binary Decision Process in Pre-Evacuation Behavior
arxiv.org·1d
A Framework for FAIR and CLEAR Ecological Data and Knowledge: Semantic Units for Synthesis and Causal Modelling
arxiv.org·1d
🧩Procedural Generation
A Physics-Driven Neural Network with Parameter Embedding for Generating Quantitative MR Maps from Weighted Images
arxiv.org·2d
🧩Procedural Generation