https://git.uwaterloo.ca/data-analytics-lab/symbolicgpt2
공식 코드SymbolicGPT: A Generative Transformer Model for Symbolic Regression
Papers with Code 아카이브
Symbolic Regression
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producing a mathematical expression (symbolic expression) that fits a given tabular data.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/1716757342/metsymnet
공식 코드MetaSymNet: A Tree-like Symbol Network with Adaptive Architecture and Activation Functions
https://github.com/1716757342/mmsr
공식 코드MMSR: Symbolic Regression is a Multi-Modal Information Fusion Task
https://github.com/AllanSCosta/occam-net
공식 코드OccamNet: A Fast Neural Model for Symbolic Regression at Scale
https://github.com/Ambrosys/glyph
공식 코드https://github.com/ColeMiles/SpectralVAE
공식 코드Machine learning of Kondo physics using variational autoencoders and symbolic regression
https://github.com/CuiHen/Reorder_Strategies_for_CGP
공식 코드Analysing the Influence of Reorder Strategies for Cartesian Genetic Programming
https://github.com/DiffEqML/torchdyn
공식 코드https://github.com/EpistasisLab/regression-benchmark
공식 코드Where are we now? A large benchmark study of recent symbolic regression methods
https://github.com/EpistasisLab/srbench
공식 코드Contemporary Symbolic Regression Methods and their Relative Performance
https://github.com/HaohanZou/CoNSAL
공식 코드Combining Neural Networks and Symbolic Regression for Analytical Lyapunov Function Discovery
https://github.com/IBM/AI-Hilbert
공식 코드Evolving Scientific Discovery by Unifying Data and Background Knowledge with AI Hilbert
https://github.com/ITMO-NSS-team/EPDE_automated_knowledge
공식 코드Knowledge-aware equation discovery with automated background knowledge extraction
https://github.com/ITMO-NSS-team/EPDE_paper_experiments
공식 코드Equation discovery framework EPDE: Towards a better equation discovery
https://github.com/IsmailAlaouiAbdellaoui/EQL-Wind-Speed-Forecasting
공식 코드Symbolic regression for scientific discovery: an application to wind speed forecasting
https://github.com/Jie0618/PhysicsRegression
공식 코드https://github.com/MaLeLabTs/GPFormulasInterpretability
공식 코드Learning a Formula of Interpretability to Learn Interpretable Formulas
https://github.com/MansoorehMontazerin/LIES
공식 코드Sparse Interpretable Deep Learning with LIES Networks for Symbolic Regression
https://github.com/MilesCranmer/PySR
공식 코드Discovering Symbolic Models from Deep Learning with Inductive Biases
https://github.com/MilesCranmer/symbolic_deep_learning
공식 코드Discovering Symbolic Models from Deep Learning with Inductive Biases
https://github.com/MustBeOne/SA-GAT-SR
공식 코드https://github.com/NISL-MSU/MultiSetSR
공식 코드Univariate Skeleton Prediction in Multivariate Systems Using Transformers
https://github.com/NewT123-WM/Task_based_neurons
공식 코드No One-Size-Fits-All Neurons: Task-based Neurons for Artificial Neural Networks
https://github.com/PaulsonLab/SyMANTIC
공식 코드https://github.com/SJ001/AI-Feynman
공식 코드AI Feynman: a Physics-Inspired Method for Symbolic Regression
https://github.com/ShuaiGuo16/PINN_symbolic_regression
공식 코드https://github.com/SymposiumOrganization/NeuralSymbolicRegressionThatScales
공식 코드https://github.com/Yuantian013/Sym-Q
공식 코드Sym-Q: Adaptive Symbolic Regression via Sequential Decision-Making
https://github.com/ailwq/dysymnet
공식 코드A Neural-Guided Dynamic Symbolic Network for Exploring Mathematical Expressions from Data
https://github.com/alpz/mech-nn
공식 코드https://github.com/ancientshi/karsein
공식 코드CTR-KAN: KAN for Adaptive High-Order Feature Interaction Modeling
https://github.com/andiva/tmpnn
공식 코드TMPNN: High-Order Polynomial Regression Based on Taylor Map Factorization
https://github.com/andrewni420/dalex
공식 코드https://github.com/astrolabsoftware/fink-science
공식 코드https://github.com/atomslab/llmsforsr
공식 코드In Context Learning and Reasoning for Symbolic Regression with Large Language Models
https://github.com/brencej/ProGED
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.