{"list":"other","total":61,"rows":[{"id":"1301.3781","title":"Efficient Estimation of Word Representations in Vector Space","created":"2013-01-16","cited_by_count":4375},{"id":"1905.11481","title":"AI Feynman: a Physics-Inspired Method for Symbolic Regression","created":"2019-05-27","cited_by_count":548},{"id":"2402.00157","title":"Large Language Models for Mathematical Reasoning: Progresses and Challenges","created":"2024-01-31","cited_by_count":284},{"id":"1912.01412","title":"Deep Learning for Symbolic Mathematics","created":"2019-12-02","cited_by_count":270},{"id":"2204.10532","title":"End-to-end symbolic regression with transformers","created":"2022-04-22","cited_by_count":203},{"id":"2212.10535","title":"A Survey of Deep Learning for Mathematical Reasoning","created":"2022-12-20","cited_by_count":124},{"id":"2405.12205","title":"Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving","created":"2024-05-20","cited_by_count":84},{"id":"2202.02306","title":"Rediscovering orbital mechanics with machine learning","created":"2022-02-04","cited_by_count":71},{"id":"2110.12773","title":"Scientific Machine Learning Benchmarks","created":"2021-10-25","cited_by_count":60},{"id":"2010.16263","title":"Learning to Unknot","created":"2020-10-28","cited_by_count":40},{"id":"2003.13679","title":"Detecting Symmetries with Neural Networks","created":"2020-03-30","cited_by_count":34},{"id":"2308.15594","title":"Learning the greatest common divisor: explaining transformer predictions","created":"2023-08-29","cited_by_count":33},{"id":"2012.15821","title":"Neural Network Approximations for Calabi-Yau Metrics","created":"2020-12-31","cited_by_count":32},{"id":"2101.06317","title":"Machine-Learning Mathematical Structures","created":"2021-01-15","cited_by_count":25},{"id":"2108.01403","title":"Nonperturbative renormalization for the neural network-QFT correspondence","created":"2021-08-03","cited_by_count":24},{"id":"1910.08605","title":"Machine learning Calabi-Yau metrics","created":"2019-10-18","cited_by_count":23},{"id":"1806.03121","title":"Machine Learning CICY Threefolds","created":"2018-06-08","cited_by_count":22},{"id":"2009.14596","title":"Machine Learning and Computational Mathematics","created":"2020-09-23","cited_by_count":22},{"id":"1706.02714","title":"Deep-Learning the Landscape","created":"2017-06-08","cited_by_count":21},{"id":"2005.01917","title":"Learning selection strategies in Buchberger's algorithm","created":"2020-05-05","cited_by_count":20},{"id":"2403.04571","title":"Machine learning and information theory concepts towards an AI Mathematician","created":"2024-03-07","cited_by_count":20},{"id":"1812.02893","title":"The Calabi-Yau Landscape: from Geometry, to Physics, to Machine-Learning","created":"2018-12-07","cited_by_count":19},{"id":"2006.10783","title":"Quiver Mutations, Seiberg Duality and Machine Learning","created":"2020-06-18","cited_by_count":19},{"id":"2007.15706","title":"Machine learning for complete intersection Calabi-Yau manifolds: a methodological study","created":"2020-07-30","cited_by_count":17},{"id":"1910.07631","title":"Machine Learning and Big Scientific Data","created":"2019-10-12","cited_by_count":16},{"id":"1905.02263","title":"Learning Algebraic Structures: Preliminary Investigations","created":"2019-05-02","cited_by_count":15},{"id":"2112.06350","title":"Machine Learning Calabi-Yau Hypersurfaces","created":"2021-12-12","cited_by_count":15},{"id":"2010.01213","title":"Machine-Learning the Sato--Tate Conjecture","created":"2020-10-02","cited_by_count":14},{"id":"2204.10140","title":"Murmurations of elliptic curves","created":"2022-04-21","cited_by_count":14},{"id":"2304.12602","title":"Is deep learning a useful tool for the pure mathematician?","created":"2023-04-25","cited_by_count":14},{"id":"2011.00871","title":"Machine Learning Lie Structures & Applications to Physics","created":"2020-11-02","cited_by_count":13},{"id":"2006.16619","title":"Graph Laplacians, Riemannian Manifolds and their Machine-Learning","created":"2020-06-30","cited_by_count":12},{"id":"2012.03955","title":"Disentangling a Deep Learned Volume Formula","created":"2020-12-07","cited_by_count":12},{"id":"2204.02704","title":"Fundamental limits to learning closed-form mathematical models from data","created":"2022-04-06","cited_by_count":12},{"id":"2402.13321","title":"Rigor with Machine Learning from Field Theory to the Poincar\\'e Conjecture","created":"2024-02-20","cited_by_count":12},{"id":"2003.04817","title":"Explore and Exploit with Heterotic Line Bundle Models","created":"2020-03-10","cited_by_count":11},{"id":"2004.05218","title":"Machine-Learning Dessins d'Enfants: Explorations via Modular and Seiberg-Witten Curves","created":"2020-04-10","cited_by_count":10},{"id":"2106.00026","title":"Machine-Learning Non-Conservative Dynamics for New-Physics Detection","created":"2021-05-31","cited_by_count":10},{"id":"2310.13021","title":"AI for Mathematics: A Cognitive Science Perspective","created":"2023-10-19","cited_by_count":10},{"id":"2310.16005","title":"MLFMF: Data Sets for Machine Learning for Mathematical Formalization","created":"2023-10-24","cited_by_count":10},{"id":"1406.1584","title":"Learning to Discover Efficient Mathematical Identities","created":"2014-06-06","cited_by_count":9},{"id":"2011.08958","title":"Machine-Learning Number Fields","created":"2020-11-17","cited_by_count":9},{"id":"2112.10872","title":"Calabi-Yau Metrics, Energy Functionals and Machine-Learning","created":"2021-12-20","cited_by_count":9},{"id":"2203.13847","title":"Cluster Algebras: Network Science and Machine Learning","created":"2022-03-25","cited_by_count":9},{"id":"1911.02008","title":"Machine Learning meets Number Theory: The Data Science of Birch-Swinnerton-Dyer","created":"2019-11-04","cited_by_count":8},{"id":"2109.01634","title":"AI Descartes: Combining Data and Theory for Derivable Scientific Discovery","created":"2021-09-03","cited_by_count":8},{"id":"2112.09117","title":"Machine Learning Kreuzer--Skarke Calabi--Yau Threefolds","created":"2021-12-16","cited_by_count":8},{"id":"2306.07277","title":"Mathematical conjecture generation using machine intelligence","created":"2023-06-12","cited_by_count":8},{"id":"1706.09451","title":"(Machine) Learning to Do More with Less","created":"2017-06-28","cited_by_count":7},{"id":"2010.14236","title":"Scientific intuition inspired by machine learning generated hypotheses","created":"2020-10-27","cited_by_count":7},{"id":"2309.05473","title":"Machine learning the dimension of a Fano variety","created":"2023-09-11","cited_by_count":7},{"id":"2312.04556","title":"Large Language Models for Mathematicians","created":"2023-12-07","cited_by_count":7},{"id":"2104.05930","title":"Distilling Wikipedia mathematical knowledge into neural network models","created":"2021-04-13","cited_by_count":6},{"id":"1805.07431","title":"Can machine learning identify interesting mathematics? An exploration using empirically observed laws","created":"2018-05-18","cited_by_count":4},{"id":"2304.07247","title":"The R-mAtrIx Net","created":"2023-04-14","cited_by_count":4},{"id":"2401.13447","title":"Symbolic Equation Solving via Reinforcement Learning","created":"2024-01-24","cited_by_count":4},{"id":"2204.11613","title":"Machine learning of the well known things","created":"2022-04-25","cited_by_count":3},{"id":"2003.10445","title":"Baryons from Mesons: A Machine Learning Perspective","created":"2020-03-23","cited_by_count":2},{"id":"2009.03192","title":"A Neural Network Perturbation Theory Based on the Born Series","created":"2020-09-07","cited_by_count":2},{"id":"1707.02800","title":"Artificial Neural Network in Cosmic Landscape","created":"2017-07-10","cited_by_count":1},{"id":"1905.08359","title":"Why Machines Cannot Learn Mathematics, Yet","created":"2019-05-20","cited_by_count":1}],"next_cursor":null}