1 citations · 4 across the 8 of their papers we have counts for
8 papers
Machine learning in and out of equilibrium
Shishir Adhikari, Alkan Kabakçıoğlu, Alexander Strang +2
The algorithms used to train neural networks, like stochastic gradient descent (SGD), have close parallels to natural processes that navigate a high-dimensional parameter space --…
Explicitly Solvable Continuous-time Inference for Partially Observed Markov Processes
Daniel Chen, Alexander G. Strang, Andrew W. Eckford +1
Many natural and engineered systems can be modeled as discrete state Markov processes. Often, only a subset of states are directly observable. Inferring the conditional probability…
Path-following methods for Maximum a Posteriori estimators in Bayesian hierarchical models: How estimates depend on hyperparameters
Zilai Si, Yucong Liu, Alexander Strang
Maximum a posteriori (MAP) estimation, like all Bayesian methods, depends on prior assumptions. These assumptions are often chosen to promote specific features in the recovered est…
Hierarchical Ensemble Kalman Methods with Sparsity-Promoting Generalized Gamma Hyperpriors
Hwanwoo Kim, Daniel Sanz-Alonso, Alexander Strang
This paper introduces a computational framework to incorporate flexible regularization techniques in ensemble Kalman methods for nonlinear inverse problems. The proposed methodolog…
Similarity Suppresses Cyclicity: Why Similar Competitors Form Hierarchies
Christopher Cebra, Alexander Strang
Competitive systems can exhibit both hierarchical (transitive) and cyclic (intransitive) structures. Despite theoretical interest in cyclic competition, which offers richer dynamic…
A Variational Inference Approach to Inverse Problems with Gamma Hyperpriors
Shiv Agrawal, Hwanwoo Kim, Daniel Sanz-Alonso +1
Hierarchical models with gamma hyperpriors provide a flexible, sparse-promoting framework to bridge and regularizations in Bayesian formulations to inverse problems. De…
The Network HHD: Quantifying Cyclic Competition in Trait-Performance Models of Tournaments
Alexander Strang, Karen C. Abbott, Peter J. Thomas
Competitive tournaments appear in sports, politics, population ecology, and animal behavior. All of these fields have developed methods for rating competitors and ranking them acco…
Relationships Between Characteristic Path Length, Efficiency, Clustering Coefficients, and Graph Density
Alexander Strang, Oliver Haynes, Nathan D. Cahill +1
The graph theoretic properties of the clustering coefficient, characteristic (or average) path length, global and local efficiency, provide valuable information regarding the struc…