A classified list of meta learning papers based on realm.
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Sep 29, 2022
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machine-learning-theory
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Learn the theory, math and code behind different machine learning algorithms and techniques.
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Jul 8, 2022 - Python
The first comprehensive Lean 4 formalization of statistical learning theory, featuring Gaussian Lipschitz concentration and Dudley's entropy integral-establishes a reusable foundation for formalizing ML theory.
formalization formal-mathematics machine-learning-theory learning-theory lean4 high-dimensional-statistics autoformalization statistical-learning-theory
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Mar 5, 2026 - Lean
This article reframes pricing as a negotiation rather than a prediction, showing how price emerges from tensions between product reality, market dynamics, and buyer behavior. It introduces negotiation-aware ML, value decomposition, and equilibrium modeling to build transparent, human-aligned pricing systems.
predictive-analytics decision-science machine-learning-theory behavioral-economics explainable-ai economic-modeling human-centered-ai pricing-strategy value-decomposition pricing-models market-dynamics transparent-ai pricing-intelligence xai-methods scenario-simulation negotiation-theory equilibrium-modeling behavioral-ml interpreter-ml ml-philosophy
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Dec 11, 2025
This article explores the theory behind explainable car pricing using value decomposition, showing how machine learning models can break a predicted price into intuitive components such as brand premium, age depreciation, mileage influence, condition effects, and transmission or fuel-type adjustments.
random-forest predictive-modeling sensitivity-analysis machine-learning-theory interpretable-ml explainable-ai model-interpretability economic-modeling feature-attribution applied-ml consumer-analytics value-decomposition data-science-methods transparent-ai pricing-intelligence automotive-analytics car-price-modeling ml-explainability automotive-ml explainable-pricing
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Dec 10, 2025 - Python
[NeurIPS 2023] The official implementation of "Rethinking Semi-Supervised Imbalanced Node Classification from Bias-Variance Decomposition" .
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Oct 25, 2025 - Python
ML course project: investigation on common perceptions of same neural network model with different random seed
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May 31, 2020 - Python
Implementation is to use gradient descent to find the optimal values of th that minimize the cost function.
python data-science machine-learning optimization supervised-learning logistic-regression regularization gradient-descent predictive-modeling theta machine-learning-theory statistical-modeling cost-function mathematical-modeling
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Jan 31, 2026 - Python
Chapter summaries adapted from the textbook "Understanding Machine Learning"
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Jan 7, 2018 - Jupyter Notebook
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Sep 20, 2022 - Jupyter Notebook
This repository hosts a progressive series of implementations (Code_v1, Code_v2, and beyond) for deterministic b*-optimization in the Information Bottleneck framework. Includes symbolic fusion, multi-path inference, and Alpay Algebra-driven critical point validation (b* = 4.14144).
statistical-inference mutual-information machine-learning-theory phase-transition information-bottleneck symbolic-algebra alpay-algebra beta-optimization deep-theory ib-framework
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May 15, 2025 - Python
A growing list of papers, books, courses and blogs related to machine learning theory and optimization
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Aug 30, 2025 - Shell
Official code repository for Distributional Autoencoders Know the Score, NeurIPS 2025
machine-learning molecular-dynamics scoring-rules computational-chemistry pca autoencoder unsupervised-learning principal-component-analysis manifold-learning machine-learning-theory distributional principal-component-analysis-pca score-matching score-based-generative-modeling neurips-2025
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Nov 28, 2025 - Jupyter Notebook
A clean, theoretical implementation of Stochastic Variance Reduced Gradient (SVRG) demonstrating linear convergence rates on convex objectives. Includes comparative analysis against vanilla SGD with empirical validation on synthetic and real-world datasets.
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Dec 15, 2025 - Jupyter Notebook
Emergent Computational Epistemology: studying AI's emergent behaviors as non-human epistemic systems.
cybernetics coherence ece epistemology machine-learning-theory interpretability emergence ai-evaluation ai-philosophy non-human-epistemes
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Sep 4, 2025 - Python
Towards understanding Machine Learning theory in 69 days :)
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Apr 22, 2025
My personal projects of re-learning machine learning and deep learning algorithms
python machine-learning computer-vision sklearn machine-learning-algorithms regression datascience classification machine-learning-theory machinelearning-python python-projects
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Oct 28, 2025 - Jupyter Notebook
Reproducing the results in "Implicit Regularization in ReLU Networks with the Square Loss" using Matlab
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Jan 31, 2022 - MATLAB
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Mar 1, 2025 - HTML
AI labs - solutions
nlp machine-learning big-data reinforcement-learning computer-vision robotics biomedical-informatics machine-learning-theory multidimensional-data
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Jun 1, 2024 - Jupyter Notebook
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