47 citations · 47 across the 1 of their papers we have counts for
5 papers
Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs
Théo Lacombe, Yuichi Ike, Mathieu Carriere +3
Although neural networks are capable of reaching astonishing performances on a wide variety of contexts, properly training networks on complicated tasks requires expertise and can…
ATOL: Measure Vectorization for Automatic Topologically-Oriented Learning
Martin Royer, Frédéric Chazal, Clément Levrard +2
Robust topological information commonly comes in the form of a set of persistence diagrams, finite measures that are in nature uneasy to affix to generic machine learning framework…
Topological Data Analysis for Arrhythmia Detection through Modular Neural Networks
Meryll Dindin, Yuhei Umeda, Frederic Chazal
This paper presents an innovative and generic deep learning approach to monitor heart conditions from ECG signals.We focus our attention on both the detection and classification of…
PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures
Mathieu Carrière, Frédéric Chazal, Yuichi Ike +3
Persistence diagrams, the most common descriptors of Topological Data Analysis, encode topological properties of data and have already proved pivotal in many different applications…
Equation of state and optical properties of shock-compressed C:H:N:O molecular mixtures
M. Guarguaglini, J. -A. Hernandez, T. Okuchi +14
Water, ethanol, and ammonia are the key components of the mantles of Uranus and Neptune. To improve structure and evolution models and give an explanation of the magnetic fields an…