271 citations · 278 across the 5 of their papers we have counts for
5 papers
SQuadMDS: a lean Stochastic Quartet MDS improving global structure preservation in neighbor embedding like t-SNE and UMAP
Pierre Lambert, Cyril de Bodt, Michel Verleysen +1
Multidimensional scaling is a statistical process that aims to embed high dimensional data into a lower-dimensional space; this process is often used for the purpose of data visual…
Perplexity-free Parametric t-SNE
Francesco Crecchi, Cyril de Bodt, Michel Verleysen +2
The t-distributed Stochastic Neighbor Embedding (t-SNE) algorithm is a ubiquitously employed dimensionality reduction (DR) method. Its non-parametric nature and impressive efficacy…
Deep Learning to Detect Bacterial Colonies for the Production of Vaccines
Thomas Beznik, Paul Smyth, Gaël de Lannoy +1
During the development of vaccines, bacterial colony forming units (CFUs) are counted in order to quantify the yield in the fermentation process. This manual task is time-consuming…
Inversion using a new low-dimensional representation of complex binary geological media based on a deep neural network
Eric Laloy, Romain Hérault, John Lee +2
Efficient and high-fidelity prior sampling and inversion for complex geological media is still a largely unsolved challenge. Here, we use a deep neural network of the variational a…
Forecasting the CATS benchmark with the Double Vector Quantization method
Geoffroy Simon, John Lee, Marie Cottrell +1
The Double Vector Quantization method, a long-term forecasting method based on the SOM algorithm, has been used to predict the 100 missing values of the CATS competition data set.…