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Model Discovery

discovering PDEs from spatiotemporal data

Papers

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Showing 1–25 of 87 papers

TitleStatusHype
AutoToM: Automated Bayesian Inverse Planning and Model Discovery for Open-ended Theory of MindCode2
PySINDy: A comprehensive Python package for robust sparse system identificationCode2
SyMANTIC: An Efficient Symbolic Regression Method for Interpretable and Parsimonious Model Discovery in Science and BeyondCode1
TorchSISSO: A PyTorch-Based Implementation of the Sure Independence Screening and Sparsifying Operator for Efficient and Interpretable Model DiscoveryCode1
Explainable Deep Learning for Tumor Dynamic Modeling and Overall Survival Prediction using Neural-ODECode1
A new family of Constitutive Artificial Neural Networks towards automated model discoveryCode1
Learning Sparse Nonlinear Dynamics via Mixed-Integer OptimizationCode1
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy dataCode1
Sparsely constrained neural networks for model discovery of PDEsCode1
Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from DataCode1
Physics-informed learning of governing equations from scarce dataCode1
Bayesian differential programming for robust systems identification under uncertaintyCode1
DeepMoD: Deep learning for Model Discovery in noisy dataCode1
Exploiting Leaderboards for Large-Scale Distribution of Malicious Models—0
Enhancing generalizability of model discovery across parameter space with multi-experiment equation learning (ME-EQL)Code0
Bi-Level optimization for parameter estimation of differential equations using interpolationCode0
Neuro-Symbolic Operator for Interpretable and Generalizable Characterization of Complex Piezoelectric Systems—0
Automated Modeling Method for Pathloss Model DiscoveryCode0
Model Discovery with Grammatical Evolution. An Experiment with Prime Numbers—0
Automatically Differentiable Model Updating (ADiMU): conventional, hybrid, and neural network material model discovery including history-dependency—0
Optimizing Hard Thresholding for Sparse Model Discovery—0
Discovering dynamical laws for speech gestures—0
Coordinated Ramp Metering Control based on Scalable Nonlinear Traffic Dynamics Model Discovery in a Large Network—0
SODAs: Sparse Optimization for the Discovery of Differential and Algebraic EquationsCode0
A Cutting Mechanics-based Machine Learning Modeling Method to Discover Governing Equations of Machining Dynamics—0
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