3 citations · 9 across the 7 of their papers we have counts for
5 papers · 1 filter
Advantages of biologically-inspired adaptive neural activation in RNNs during learning
Victor Geadah, Giancarlo Kerg, Stefan Horoi +2
Dynamic adaptation in single-neuron response plays a fundamental role in neural coding in biological neural networks. Yet, most neural activation functions used in artificial netwo…
Supervised Visualization for Data Exploration
Jake S. Rhodes, Adele Cutler, Guy Wolf +1
Dimensionality reduction is often used as an initial step in data exploration, either as preprocessing for classification or regression or for visualization. Most dimensionality re…
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence
Bastian Rieck, Tristan Yates, Christian Bock +4
Functional magnetic resonance imaging (fMRI) is a crucial technology for gaining insights into cognitive processes in humans. Data amassed from fMRI measurements result in volumetr…
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics
Alexander Tong, Jessie Huang, Guy Wolf +2
It is increasingly common to encounter data from dynamic processes captured by static cross-sectional measurements over time, particularly in biomedical settings. Recent attempts t…
Internal representation dynamics and geometry in recurrent neural networks
Stefan Horoi, Guillaume Lajoie, Guy Wolf
The efficiency of recurrent neural networks (RNNs) in dealing with sequential data has long been established. However, unlike deep, and convolution networks where we can attribute…