Medieval Scripts, Character Recognition, Historical Manuscripts, Neural Networks

Monument Engine: Jx
monument.ai·4h·
Discuss: Lobsters
SIMD Vectorization
[R] A Unified Framework for Continual Semantic Segmentation in 2D and 3D Domains
reddit.com·1d·
📝Document Chunking
How the Rise of Tabular Foundation Models Is Reshaping Data Science
towardsdatascience.com·2d
🧠Machine Learning
Automated Fault Isolation & Healing in Linear Control Systems via Multi-Modal Data Fusion & Reinforcement Learning
dev.to·13h·
Discuss: DEV
🛡️Error Boundaries
Randomized and quantum approximate matrix multiplication
arxiv.org·1d
🔐Quantum Cryptography
Deep Learning Based Approach to Enhanced Recognition of Emotions and Behavioral Patterns of Autistic Children
arxiv.org·1d
🤖Advanced OCR
SliceFine: The Universal Winning-Slice Hypothesis for Pretrained Networks
arxiv.org·1d
🧠Neural Codecs
Optimal Stopping in Latent Diffusion Models
arxiv.org·1d
🧠Machine Learning
Adaptive Kernel Regression with Spatio-Temporal Context for Real-Time Object Tracking in Aerial Imagery
dev.to·3h·
Discuss: DEV
🌀Differential Geometry
ChainMPQ: Interleaved Text-Image Reasoning Chains for Mitigating Relation Hallucinations
arxiv.org·2d
🧮Kolmogorov Complexity
StruSR: Structure-Aware Symbolic Regression with Physics-Informed Taylor Guidance
arxiv.org·2d
🧠Machine Learning
TRIM: Token-wise Attention-Derived Saliency for Data-Efficient Instruction Tuning
arxiv.org·2d
🔨Compilers
Beyond Vector Search: Building a RAG That *Actually* Understands Your Data
dev.to·2d·
Discuss: DEV
🗂️Vector Databases
From Neural Activity to Computation: Biological Reservoirs for Pattern Recognition in Digit Classification
arxiv.org·3d
🔲Cellular Automata
Unraveling LCRE-Mediated Chromatin Loops: A Predictive Model for Gene Expression Fine-Tuning in Desert Genomes
dev.to·20h·
Discuss: DEV
📥Feed Aggregation
[R] DeepSeek 3.2's sparse attention mechanism
reddit.com·1d·
🌀Brotli Internals
The Custom Conveyor: Building Your Own Iterators
dev.to·15h·
Discuss: DEV
🔄Burrows-Wheeler
GNN Blind Spots: The Hidden Cost of Powerful Graph Models
dev.to·17h·
Discuss: DEV
🕸️Graph Embeddings