research
∙
11/07/2022
Highly over-parameterized classifiers generalize since bad solutions are rare
We study the generalization of over-parameterized classifiers where Empi...
share
research
∙
05/18/2022
Large Neural Networks Learning from Scratch with Very Few Data and without Regularization
Recent findings have shown that Neural Networks generalize also in over-...
research
∙
11/09/2020
Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning
This paper explores how well deep learning models trained on chest CT im...
research
∙
08/18/2020
Feature Products Yield Efficient Networks
We introduce Feature-Product networks (FP-nets) as a novel deep-network ...
research
∙
03/25/2020
Solving Raven's Progressive Matrices with Multi-Layer Relation Networks
Raven's Progressive Matrices are a benchmark originally designed to test...
research
∙
11/05/2018
Multi-layer Relation Networks
Relational Networks (RN) as introduced by Santoro et al. (2017) have dem...
research
∙
10/06/2017
Deep Convolutional Neural Networks as Generic Feature Extractors
Recognizing objects in natural images is an intricate problem involving ...
research
∙
06/02/2016
Recursive Autoconvolution for Unsupervised Learning of Convolutional Neural Networks
In visual recognition tasks, such as image classification, unsupervised ...
research
∙
06/23/2014
Committees of deep feedforward networks trained with few data
Deep convolutional neural networks are known to give good results on ima...
research
∙
11/04/1999