3 citations · 3 across the 1 of their papers we have counts for
4 papers
On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools
Ryan Vogt, Maximilian Puelma Touzel, Eli Shlizerman +1
Recurrent neural networks (RNNs) have been successfully applied to a variety of problems involving sequential data, but their optimization is sensitive to parameter initialization,…
Inferring the immune response from repertoire sequencing
Maximilian Puelma Touzel, Aleksandra M. Walczak, Thierry Mora
High-throughput sequencing of B- and T-cell receptors makes it possible to track immune repertoires across time, in different tissues, and in acute and chronic diseases or in healt…
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics
Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel +4
A recent strategy to circumvent the exploding and vanishing gradient problem in RNNs, and to allow the stable propagation of signals over long time scales, is to constrain recurren…
Precise tracking of vaccine-responding T-cell clones reveals convergent and personalized response in identical twins
Mikhail V. Pogorelyy, Anastasia A. Minervina, Maximilian Puelma Touzel +11
T-cell receptor (TCR) repertoire data contain information about infections that could be used in disease diagnostics and vaccine development, but extracting that information remain…