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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
DeepMoD: Deep learning for Model Discovery in noisy dataCode1
SyMANTIC: An Efficient Symbolic Regression Method for Interpretable and Parsimonious Model Discovery in Science and BeyondCode1
Explainable Deep Learning for Tumor Dynamic Modeling and Overall Survival Prediction using Neural-ODECode1
Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from DataCode1
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy dataCode1
Physics-informed learning of governing equations from scarce dataCode1
Sparsely constrained neural networks for model discovery of PDEsCode1
TorchSISSO: A PyTorch-Based Implementation of the Sure Independence Screening and Sparsifying Operator for Efficient and Interpretable Model DiscoveryCode1
Learning Sparse Nonlinear Dynamics via Mixed-Integer OptimizationCode1
Bayesian differential programming for robust systems identification under uncertaintyCode1
A new family of Constitutive Artificial Neural Networks towards automated model discoveryCode1
Automatically Differentiable Model Updating (ADiMU): conventional, hybrid, and neural network material model discovery including history-dependency—0
Automated Statistical Model Discovery with Language Models—0
Optimal Pricing for Data-Augmented AutoML Marketplaces—0
Automated Model Discovery for Tensional Homeostasis: Constitutive Machine Learning in Growth and Remodeling—0
A Competitive Learning Approach for Specialized Models: A Solution for Complex Physical Systems with Distinct Functional Regimes—0
Discovering dynamical laws for speech gestures—0
Convergence of uncertainty estimates in Ensemble and Bayesian sparse model discovery—0
A Unified Framework for Sparse Relaxed Regularized Regression: SR3—0
Coordinated Ramp Metering Control based on Scalable Nonlinear Traffic Dynamics Model Discovery in a Large Network—0
Causal Inductive Synthesis Corpus—0
Causal KL: Evaluating Causal Discovery—0
A Cutting Mechanics-based Machine Learning Modeling Method to Discover Governing Equations of Machining Dynamics—0
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