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Information, Physics, and Computation (Oxford Graduate Texts): Mézard, Marc, Montanari, Andrea: 8601410201722: Amazon.com: Books
amazon.com·1d
🧮Kolmogorov Complexity
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Generative Latent Coding for Ultra-Low Bitrate Image Compression
arxiv.org·4d
🧠Neural Codecs
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Behold the Manifold, the Concept that Changed How Mathematicians View Space
wired.com·17m
🌀Differential Geometry
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What I Learned Building a Storage Engine That Outperforms RocksDB
tidesdb.com·8h·
🦀Rusty Databases
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Treating Functions as Vectors in Hilbert Space
hackaday.com·2d
📐Linear Algebra
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What You Need to Know Before Touching a Video File
gist.github.com·12h·
Discuss: Hacker News
🎥Streaming Codecs
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Keeping Probabilities Honest: The Jacobian Adjustment
towardsdatascience.com·2d
🎯Arithmetic Coding Theory
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Gaussian concentration bounds for probabilistic cellular automata | Journal of Statistical Physics
link.springer.com·1d
🔲Cellular Automata
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Opening the Black Box of Deep Neural Networks via Information
paperium.net·1d·
Discuss: DEV
🧠Machine Learning
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Algebraic Topology 1: Homotopy Equivalence
youtube.com·16h
🕸️Algebraic Topology
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Natural language processing for word sense disambiguation and information extraction
arxiv.org·22h·
Discuss: r/compsci
📥Feed Aggregation
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What Deep Learning Theory Teaches Us About AI Memory
dev.to·1d·
Discuss: DEV
🧠Learned Compression
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Mathematicians spent 2025 exploring the edge of mathematics
newscientist.com·1d
📚Archive Mathematics
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Courses with certificates
codefinity.com·1d
🧠Neural Codecs
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Book Review: Why Machines Learn
philippdubach.com·1d·
Discuss: Hacker News
🧠Machine Learning
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Overengineering float serialization for no good reason
wejn.org·2d
🧪Binary Fuzzing
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Anticipating Risk Before It Hits: Surbhi Gupta on the Future of Predictive Analytics
hackernoon.com·2d
🔍BitFunnel
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Stanford CS 224N | Natural Language Processing with Deep Learning
web.stanford.edu·1d
🧠Machine Learning
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Bit rot and cloud storage (commercial or homelab)
reddit.com·1d·
Discuss: r/homelab
🏠Homelab Preservation
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