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LLM & AI Agent Applications with LangChain and LangGraph — Part 4 — Components of GPT
pub.towardsai.net·3h
🤖Grammar Induction
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Keeping Probabilities Honest: The Jacobian Adjustment
towardsdatascience.com·2d
🎯Arithmetic Coding
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Everything Is a Number
francescocarlucci.com·1d·
Discuss: Hacker News
💎Information Crystallography
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Information, Physics, and Computation (Oxford Graduate Texts): Mézard, Marc, Montanari, Andrea: 8601410201722: Amazon.com: Books
amazon.com·1d
📐Compression Mathematics
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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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Treating Functions as Vectors in Hilbert Space
hackaday.com·2d
📐Linear Algebra
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Running Code and Failing Models – Rajiv Shah
projects.rajivshah.com·2d
🧠Machine Learning
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What Deep Learning Theory Teaches Us About AI Memory
dev.to·1d·
Discuss: DEV
🧠Learned Compression
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Measuring True Campaign Uplift in Noisy E-Commerce Data: A Practical Heuristic Approach
hackernoon.com·1d
📊Feed Optimization
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Mathematicians spent 2025 exploring the edge of mathematics
newscientist.com·1d
📚Archive Mathematics
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Opening the Black Box of Deep Neural Networks via Information
paperium.net·1d·
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🧠Machine Learning
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Human Processor Model
en.wikipedia.org·1d·
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🧠Intelligence Compression
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A New Twist in a Famous Problem
blog.tanyakhovanova.com·1d
🔲Cellular Automata
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Performance Hints for BigQuery
trmlabs.com·11h·
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🚀Query Optimization
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Courses with certificates
codefinity.com·1d
🧠Neural Codecs
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Understanding Automata Theory Through Route Maps
dev.to·2h·
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🎯Automata theory
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Variationally correct operator learning: Reduced basis neural operator with a posteriori error estimation
arxiv.org·3d
🧠Machine Learning
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Attention from First Principles
metaworld.me·4d·
🧠Machine Learning
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Overengineering float serialization for no good reason
wejn.org·2d
🧪Binary Fuzzing
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The Transformer Architecture: A Deep Dive into How LLMs Actually Work
dev.to·11h·
Discuss: DEV
📝Text Parsing
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