33 citations · 47 across the 4 of their papers we have counts for
4 papers
Bayesian Mixed Effects Models for Zero-inflated Compositions in Microbiome Data Analysis
Boyu Ren, Sergio Bacallado, Stefano Favaro +3
Detecting associations between microbial compositions and sample characteristics is one of the most important tasks in microbiome studies. Most of the existing methods apply univar…
Pushing Stochastic Gradient towards Second-Order Methods -- Backpropagation Learning with Transformations in Nonlinearities
Tommi Vatanen, Tapani Raiko, Harri Valpola +1
Recently, we proposed to transform the outputs of each hidden neuron in a multi-layer perceptron network to have zero output and zero slope on average, and use separate shortcut co…
Semi-Supervised Anomaly Detection - Towards Model-Independent Searches of New Physics
Mikael Kuusela, Tommi Vatanen, Eric Malmi +3
Most classification algorithms used in high energy physics fall under the category of supervised machine learning. Such methods require a training set containing both signal and ba…
Soft Classification of Diffractive Interactions at the LHC
Mikael Kuusela, Eric Malmi, Risto Orava +1
Multivariate machine learning techniques provide an alternative to the rapidity gap method for event-by-event identification and classification of diffraction in hadron-hadron coll…