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09/03/2023
Implicit regularization of deep residual networks towards neural ODEs
Residual neural networks are state-of-the-art deep learning models. Thei...
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05/02/2023
Convergence and error analysis of PINNs
Physics-informed neural networks (PINNs) are a promising approach that c...
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04/04/2023
The insertion method to invert the signature of a path
The signature is a representation of a path as an infinite sequence of i...
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06/14/2022
Scaling ResNets in the Large-depth Regime
Deep ResNets are recognized for achieving state-of-the-art results in co...
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01/08/2022
Optimal 1-Wasserstein Distance for WGANs
The mathematical forces at work behind Generative Adversarial Networks r...
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06/02/2021
Framing RNN as a kernel method: A neural ODE approach
Building on the interpretation of a recurrent neural network (RNN) as a ...
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05/25/2021
SHAFF: Fast and consistent SHApley eFfect estimates via random Forests
Interpretability of learning algorithms is crucial for applications invo...
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06/09/2020
Approximating Lipschitz continuous functions with GroupSort neural networks
Recent advances in adversarial attacks and Wasserstein GANs have advocat...
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06/08/2020
Wasserstein Random Forests and Applications in Heterogeneous Treatment Effects
We present new insights into causal inference in the context of Heteroge...
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06/04/2020
Some Theoretical Insights into Wasserstein GANs
Generative Adversarial Networks (GANs) have been successful in producing...
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04/29/2020
Interpretable Random Forests via Rule Extraction
We introduce SIRUS (Stable and Interpretable RUle Set) for regression, a...
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08/19/2019
SIRUS: making random forests interpretable
State-of-the-art learning algorithms, such as random forests or neural n...
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03/06/2018
Accelerated Gradient Boosting
Gradient tree boosting is a prediction algorithm that sequentially produ...
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04/25/2016
Neural Random Forests
Given an ensemble of randomized regression trees, it is possible to rest...
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11/18/2015
A Random Forest Guided Tour
The random forest algorithm, proposed by L. Breiman in 2001, has been ex...
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07/16/2014
Online Asynchronous Distributed Regression
Distributed computing offers a high degree of flexibility to accommodate...
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05/12/2014
Consistency of random forests
Random forests are a learning algorithm proposed by Breiman [Mach. Learn...
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01/20/2013
Cellular Tree Classifiers
The cellular tree classifier model addresses a fundamental problem in th...
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10/13/2009
