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Model Discovery

discovering PDEs from spatiotemporal data

Papers

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Showing 1–50 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
NOMTO: Neural Operator-based symbolic Model approximaTion and discOvery—0
BoxingGym: Benchmarking Progress in Automated Experimental Design and Model DiscoveryCode0
Automated Model Discovery for Tensional Homeostasis: Constitutive Machine Learning in Growth and Remodeling—0
AutoTurb: Using Large Language Models for Automatic Algebraic Model Discovery of Turbulence Closure—0
Towards Model Discovery Using Domain Decomposition and PINNsCode0
Data-driven model discovery with Kolmogorov-Arnold networks—0
HyTAS: A Hyperspectral Image Transformer Architecture Search Benchmark and AnalysisCode0
GN-SINDy: Greedy Sampling Neural Network in Sparse Identification of Nonlinear Partial Differential Equations—0
Scalable Sparse Regression for Model Discovery: The Fast Lane to InsightCode0
Discovering intrinsic multi-compartment pharmacometric models using Physics Informed Neural Networks—0
Automated Statistical Model Discovery with Language Models—0
Operator Learning: Algorithms and Analysis—0
Process mining for self-regulated learning assessment in e-learning—0
Optimal Pricing for Data-Augmented AutoML Marketplaces—0
Exploring hyperelastic material model discovery for human brain cortex: multivariate analysis vs. artificial neural network approaches—0
On sparse regression, Lp-regularization, and automated model discovery—0
HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations—0
Extreme sparsification of physics-augmented neural networks for interpretable model discovery in mechanics—0
Naming Practices of Pre-Trained Models in Hugging Face—0
End-to-end Phase Field Model Discovery Combining Experimentation, Crowdsourcing, Simulation and Learning—0
Adaptive Uncertainty-Guided Model Selection for Data-Driven PDE DiscoveryCode0
A Competitive Learning Approach for Specialized Models: A Solution for Complex Physical Systems with Distinct Functional Regimes—0
The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence—0
Efficient hybrid modeling and sorption model discovery for non-linear advection-diffusion-sorption systems: A systematic scientific machine learning approachCode0
Auxiliary Functions as Koopman Observables: Data-Driven Analysis of Dynamical Systems via Polynomial OptimizationCode0
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