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06/08/2023
A Meta-Generation framework for Industrial System Generation
Generative design is an increasingly important tool in the industrial wo...
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04/08/2023
Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification
We consider the problem of uncertainty quantification in high dimensiona...
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12/22/2022
Fixed-budget online adaptive mesh learning for physics-informed neural networks. Towards parameterized problem inference
Physics-Informed Neural Networks (PINNs) have gained much attention in v...
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10/07/2022
To tree or not to tree? Assessing the impact of smoothing the decision boundaries
When analyzing a dataset, it can be useful to assess how smooth the deci...
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09/09/2022
Fast and Accurate Importance Weighting for Correcting Sample Bias
Bias in datasets can be very detrimental for appropriate statistical est...
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01/31/2022
Physics-informed neural networks for non-Newtonian fluid thermo-mechanical problems: an application to rubber calendering process
Physics-Informed Neural Networks (PINNs) have gained much attention in v...
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12/17/2021
A Binded VAE for Inorganic Material Generation
Designing new industrial materials with desired properties can be very e...
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07/07/2021
ADAPT : Awesome Domain Adaptation Python Toolbox
ADAPT is an open-source python library providing the implementation of s...
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03/05/2021
Discrepancy-Based Active Learning for Domain Adaptation
The goal of the paper is to design active learning strategies which lead...
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06/20/2020
Model family selection for classification using Neural Decision Trees
Model selection consists in comparing several candidate models according...
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06/15/2020
Adversarial Weighting for Domain Adaptation in Regression
We present a novel instance based approach to handle regression tasks in...
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09/20/2019
A clusterwise supervised learning procedure based on aggregation of distances
Nowadays, many machine learning procedures are available on the shelve a...
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09/20/2019
Consensual aggregation of clusters based on Bregman divergences to improve predictive models
A new procedure to construct predictive models in supervised learning pr...
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03/08/2018
Aggregation using input-output trade-off
In this paper, we introduce a new learning strategy based on a seminal i...
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10/04/2016