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awesome-ai-for-math

Awesome

A curated list of 62 awesome papers exploring the use of artificial intelligence / machine learning / deep learning for mathematical discoveries.

See CONTRIBUTING.md for contribution.

  • By years, there are
    • 2 papers in 2017
    • 1 paper in 2019
    • 5 papers in 2021
    • 5 papers in 2022
    • 7 papers in 2023
    • 18 papers in 2024
    • 24 papers in 2025
  • 30 of them are open-sourced.
Title Subject(s) Venue & Year Links & Resources
A Machine Learning Approach That Beats Large Rubik's Cubes Graph Theory, Group Theory, RL arXiv 2025 Code
Advancing mathematics by guiding human intuition with AI Knot Theory, Representation Theory Nature 2021 Code
AI-driven research in pure mathematics and theoretical physics Survey Nature Reviews Physics 2025
Algorithm-assisted discovery of an intrinsic order among mathematical constants Number Theory PNAS 2024 Code
AlphaEvolve: A coding agent for scientific and algorithmic discovery Matrix Multiplication, Analysis, Combinatorics, Discrete Geometry, LLM arXiv 2025 Unofficial Code
AlphaTensor: Discovering faster matrix multiplication algorithms Matrix Multiplication, RL Nature 2022 Code Blog
An algorithm for Aubert-Zelevinsky duality à la Mœglin-Waldspurger Representation Theory, Neural Network arXiv 2025 Code
An ML approach to resolution of singularities Algebraic Geometry, RL TAG-ML 2023 Code
Automated Search for Conjectures on Mathematical Constants using Analysis of Integer Sequences Number Theory ICML 2023 Code
Can Transformers Do Enumerative Geometry? Algebraic Geometry, Interpretability, Transformer ICLR 2025 Code
CayleyPy RL: Pathfinding and Reinforcement Learning on Cayley Graphs Graph Theory, Group Theory, RL arXiv 2025 Code
Constructions in combinatorics via neural networks Graph Theory, RL arXiv 2021 Code
Counterexample to majority optimality in NICD with erasures Analysis, LLM arXiv 2025
Data-scientific study of Kronecker coefficients Representation Theory, PCA Experimental Mathematics 2023
Discovery of Unstable Singularities Analysis, PINN arXiv 2025
Forbidden Sidon subsets of perfect difference sets, featuring a human-assisted proof Combinatorics, LLM arXiv 2025 Code
From Euler to AI: Unifying Formulas for Mathematical Constants Number Theory, LLM arXiv 2025 Code
Generating conjectures on fundamental constants with the Ramanujan Machine Number Theory Nature 2021 Code
Generative AI for brane configurations and coamoeba Mathematical Physics, VAE Physical Review D 2025
Geometric Generality of Transformer-Based Gröbner Basis Computation Algebraic Geometry, Transformer arXiv 2025
Global Lyapunov functions: a long-standing open problem in mathematics, with symbolic transformers Analysis, Transformer NeurIPS 2024 Code
Hilbert series, machine learning, and applications to physics Algebraic Geometry, Mathematical Physics, Neural Network Physics Letters B 2024 Code
Int2Int: a framework for mathematics with transformers Number Theory, Transformer arXiv 2025 Code
Interpretable Machine Learning for Kronecker Coefficients Representation Theory, Neural Network, Symbolic Regression, PCA, Transformer arXiv 2025
Lattice-Valued Bottleneck Duality Combinatorics arXiv 2024
Learning Euler factors of elliptic curves Number Theory, Transformer arXiv 2025
Learning Fricke signs from Maass form Coefficients Number Theory, LDA arXiv 2025
Learning to compute Gröbner Basis Algebraic Geometry, Transformer NeurIPS 2024 Code
Machine Learning Approaches to the Shafarevich-Tate Group of Elliptic Curves Number Theory, Neural Network, Decision Tree IJDSMS 2024 Code
Machine learning assisted exploration for affine Deligne-Lusztig varieties Number Theory, Representation Theory Peking Math J 2024 Code
Machine learning BPS spectra and the gap conjecture Mathematical Physics, PCA Physical Review D 2024
Machine learning Calabi-Yau hypersurfaces Mathematical Physics Physical Review D 2022
Machine learning class numbers of real quadratic fields Number Theory, Interpretability IJDSMS 2023
Machine learning for complete intersection Calabi-Yau manifolds: a methodological study Mathematical Physics Physical Review D 2021
Machine Learning in the String Landscape Mathematical Physics JHEP 2017
Machine learning invariants of arithmetic curves Number Theory, Logistic Regression, Random Forest Journal of Symbolic Computation 2023
Machine Learning Kreuzer–Skarke Calabi–Yau Threefolds Mathematical Physics, Algebraic Geometry, Neural Network arXiv 2025
Machine learning Kronecker coefficients Representation Theory, CNN, Decision Tree IJDSMS 2023
Machine learning line bundle cohomologies of hypersurfaces in toric varieties Algebraic Geometry Physics Letters B 2019
Machine Learning Number Fields Number Theory, Neural Network, Random Forest MCGD 2022
Machine learning of Calabi-Yau volumes Mathematical Physics, CNN, Linear Regression Physical Review D 2017
Machine learning Sasakian G2 topology on contact Calabi-Yau 7-manifolds Mathematical Physics, Neural Network Physics Letters B 2024 Code
Machine Learning the vanishing order of rational L-functions Number Theory, LDA, Neural Network arXiv 2025
Machine-learning dessins d'enfants: explorations via modular and Seiberg–Witten curves Algebraic Geometry, Mathematical Physics Journal of Physics A 2021
Machine-learning Sato-Tate conjecture Number Theory Journal of Symbolic Computation 2022
Machines Learn Number Fields, But How? The Case of Galois Groups Number Theory, Logistic Regression, Decision Tree, Interpretability arXiv 2025 Code
Mathematical discoveries from program search with large language models Combinatorics, LLM Nature 2024 Code
Mathematical discovery in the age of artificial intelligence Survey Nature Physics 2025
Mathematical exploration and discovery at scale Combinatorics, Analysis, Number Theory, Discrete Geometry, LLM arXiv 2025 Code
Murmurations of Elliptic Curves Number Theory, PCA Experimental Mathematics 2024 Quanta
Neural network approximations for Calabi-Yau metrics Mathematical Physics, Neural Network JHEP 2022
New Calabi–Yau manifolds from genetic algorithms Algebraic Geometry, Mathematical Physics, Genetic Algorithm Physics Letters B 2024
PatternBoost: Constructions in Mathematics with a Little Help from AI Discrete Geometry, Combinatorics, Transformer, RL arXiv 2024 Code
Point Convergence of Nesterov's Accelerated Gradient Method: An AI-Assisted Proof Analysis, LLM arXiv 2025
Predicting root numbers with neural networks Number Theory, RNN, CNN IJDSMS 2024
Ranks of elliptic curves and deep neural networks Number Theory, CNN Research in Number Theory 2023 Code
Reinforcement Learning the Chromatic Symmetric Function Graph Theory, RL arXiv 2024 Code
Rigor with Machine Learning from Field Theory to the Poincaré Conjecture Geometry, Mathematical Physics Nature Reviews Physics 2024
Searching for ribbons with machine learning Geometry, Bayesian Optimization, RL, Neural Network Machine Learning Science and Technology 2025 Code
Studying number theory with deep learning: a case study with the Möbius and squarefree indicator functions Number Theory, Transformer arXiv 2025 Code
Unsupervised Discovery of Formulas for Mathematical Constants Number Theory NeurIPS 2024 Code
What makes math problems hard for reinforcement learning: a case study Group Theory, RL, Transformer arXiv 2024 Code

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List of awesome works that use AI for mathematical discoveries.

seewoo5.github.io/awesome-ai-for-math/

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