Inception neural network for complete intersection Calabi–Yau 3-folds

On Genus-1 Gromov-Witten Invariants of Complete Intersection 3-Folds

On Genus-1 Gromov-Witten Invariants of Complete Intersection 3-Folds

Improved Inception-Residual Convolutional Neural Network for Object Recognition

Machine learning and computer vision have driven many of the greatest advances in the modeling of Deep Convolutional Neural Networks (DCNNs). Nowadays, most of the research has been focused on improving recognition accuracy with better DCNN models and learning approaches. The recurrent convolutional approach is not applied very much, other than in a few DCNN architectures. On the other hand, In...

Inception Recurrent Convolutional Neural Network for Object Recognition

Deep convolutional neural networks (DCNNs) are an influential tool for solving various problems in the machine learning and computer vision fields. In this paper, we introduce a new deep learning model called an InceptionRecurrent Convolutional Neural Network (IRCNN), which utilizes the power of an inception network combined with recurrent layers in DCNN architecture. We have empirically evalua...

Complete intersection for equivariant models

Phylogenetic varieties related to equivariant substitution models have been studied largely in the last years. One of the main objectives has been finding a set of generators of the ideal of these varieties, but this has not yet been achieved in some cases (for example, for the general Markov model this involves the open “salmon conjecture”, see [2]) and it is not clear how to use all generator...