research
∙
02/22/2023
Neural-based classification rule learning for sequential data
Discovering interpretable patterns for classification of sequential data...
share
research
∙
01/17/2022
Differentiable Rule Induction with Learned Relational Features
Rule-based decision models are attractive due to their interpretability....
research
∙
09/24/2021
Discovering PDEs from Multiple Experiments
Automated model discovery of partial differential equations (PDEs) usual...
research
∙
06/22/2021
Sparsistent Model Discovery
Discovering the partial differential equations underlying a spatio-tempo...
research
∙
06/09/2021
Fully differentiable model discovery
Model discovery aims at autonomously discovering differential equations ...
research
∙
05/02/2021
Model discovery in the sparse sampling regime
To improve the physical understanding and the predictions of complex dyn...
research
∙
11/09/2020
Sparsely constrained neural networks for model discovery of PDEs
Sparse regression on a library of candidate features has developed as th...
research
∙
12/19/2019
Temporal Normalizing Flows
Analyzing and interpreting time-dependent stochastic data requires accur...
research
∙
04/20/2019