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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
Bayesian differential programming for robust systems identification under uncertaintyCode1
A new family of Constitutive Artificial Neural Networks towards automated model discoveryCode1
Learning Sparse Nonlinear Dynamics via Mixed-Integer OptimizationCode1
Sparsely constrained neural networks for model discovery of PDEsCode1
Physics-informed learning of governing equations from scarce dataCode1
SyMANTIC: An Efficient Symbolic Regression Method for Interpretable and Parsimonious Model Discovery in Science and BeyondCode1
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy dataCode1
TorchSISSO: A PyTorch-Based Implementation of the Sure Independence Screening and Sparsifying Operator for Efficient and Interpretable Model DiscoveryCode1
Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from DataCode1
Explainable Deep Learning for Tumor Dynamic Modeling and Overall Survival Prediction using Neural-ODECode1
DeepMoD: Deep learning for Model Discovery in noisy dataCode1
Auxiliary Functions as Koopman Observables: Data-Driven Analysis of Dynamical Systems via Polynomial OptimizationCode0
Scalable Sparse Regression for Model Discovery: The Fast Lane to InsightCode0
HyTAS: A Hyperspectral Image Transformer Architecture Search Benchmark and AnalysisCode0
SODAs: Sparse Optimization for the Discovery of Differential and Algebraic EquationsCode0
Sparsistent Model DiscoveryCode0
Interpretable Scientific Discovery with Symbolic Regression: A ReviewCode0
Discovering PDEs from Multiple ExperimentsCode0
Towards Model Discovery Using Domain Decomposition and PINNsCode0
Bi-Level optimization for parameter estimation of differential equations using interpolationCode0
Learning Equations from Biological Data with Limited Time SamplesCode0
Learning normal form autoencoders for data-driven discovery of universal,parameter-dependent governing equationsCode0
Discrepancy Modeling Framework: Learning missing physics, modeling systematic residuals, and disambiguating between deterministic and random effectsCode0
Efficient hybrid modeling and sorption model discovery for non-linear advection-diffusion-sorption systems: A systematic scientific machine learning approachCode0
Model discovery in the sparse sampling regimeCode0
BoxingGym: Benchmarking Progress in Automated Experimental Design and Model DiscoveryCode0
Automated Modeling Method for Pathloss Model DiscoveryCode0
Enhancing generalizability of model discovery across parameter space with multi-experiment equation learning (ME-EQL)Code0
A toolkit for data-driven discovery of governing equations in high-noise regimesCode0
DeepArchitect: Automatically Designing and Training Deep ArchitecturesCode0
Adaptive Uncertainty-Guided Model Selection for Data-Driven PDE DiscoveryCode0
HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations—0
Learning Cognitive Models using Neural Networks—0
Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems—0
Learning Sparse Causal Models is not NP-hard—0
Mining Local Process Models—0
Model Discovery with Grammatical Evolution. An Experiment with Prime Numbers—0
Neural Activation Constellations: Unsupervised Part Model Discovery with Convolutional Networks—0
Neuro-Reachability of Networked Microgrids—0
Neuro-Symbolic Operator for Interpretable and Generalizable Characterization of Complex Piezoelectric Systems—0
NOMTO: Neural Operator-based symbolic Model approximaTion and discOvery—0
On sparse regression, Lp-regularization, and automated model discovery—0
Operator Learning: Algorithms and Analysis—0
Optimizing Hard Thresholding for Sparse Model Discovery—0
OrgMining 2.0: A Novel Framework for Organizational Model Mining from Event Logs—0
Pre and Post Counting for Scalable Statistical-Relational Model Discovery—0
Precision and Fitness in Object-Centric Process Mining—0
Process mining for self-regulated learning assessment in e-learning—0
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