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Model Discovery

discovering PDEs from spatiotemporal data

Papers

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Showing 26–50 of 87 papers

TitleStatusHype
A Nonparametric Bayesian Approach to Acoustic Model Discovery—0
Anvaya: An Algorithm and Case-Study on Improving the Goodness of Software Process Models generated by Mining Event-Log Data in Issue Tracking System—0
A Unified Framework for Sparse Relaxed Regularized Regression: SR3—0
Automated Model Discovery for Tensional Homeostasis: Constitutive Machine Learning in Growth and Remodeling—0
Automated Statistical Model Discovery with Language Models—0
Automatically Differentiable Model Updating (ADiMU): conventional, hybrid, and neural network material model discovery including history-dependency—0
Automatic Discovery of Multi-perspective Process Model using Reinforcement Learning—0
AutoTurb: Using Large Language Models for Automatic Algebraic Model Discovery of Turbulence Closure—0
Causal Inductive Synthesis Corpus—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
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
Proof Supplement - Learning Sparse Causal Models is not NP-hard (UAI2013)—0
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