4 citations · 7 across the 4 of their papers we have counts for
9 papers
Dynamical Isometry for Residual Networks
Advait Gadhikar, Rebekka Burkholz
The training success, training speed and generalization ability of neural networks rely crucially on the choice of random parameter initialization. It has been shown for multiple a…
Convolutional and Residual Networks Provably Contain Lottery Tickets
Rebekka Burkholz
The Lottery Ticket Hypothesis continues to have a profound practical impact on the quest for small scale deep neural networks that solve modern deep learning tasks at competitive p…
Scaling up Continuous-Time Markov Chains Helps Resolve Underspecification
Alkis Gotovos, Rebekka Burkholz, John Quackenbush +1
Modeling the time evolution of discrete sets of items (e.g., genetic mutations) is a fundamental problem in many biomedical applications. We approach this problem through the lens…
Cascade Size Distributions: Why They Matter and How to Compute Them Efficiently
Rebekka Burkholz, John Quackenbush
Cascade models are central to understanding, predicting, and controlling epidemic spreading and information propagation. Related optimization, including influence maximization, mod…
International crop trade networks: The impact of shocks and cascades
Rebekka Burkholz, Frank Schweitzer
Analyzing available FAO data from 176 countries over 21 years, we observe an increase of complexity in the international trade of maize, rice, soy, and wheat. A larger number of co…
Efficient message passing for cascade size distributions on finite trees
Rebekka Burkholz
How big is the risk that a few initial failures of networked nodes amplify to large cascades that endanger the functioning of the system? Common answers refer to the average final…