833 citations · 1.6k across the 22 of their papers we have counts for
25 papers
Neural Variability Enhances Artificial Network Robustness
Robin Preble, Praveen Venkatesh, Stefan Mihalas +1
Neural responses in cortex exhibit substantial trial-to-trial variability in response to repeated stimuli, while peripheral sensory neurons respond far more consistently, leading m…
Spectral gap-based deterministic tensor completion
Kameron Decker Harris, Oscar López, Angus Read +1
Tensor completion is a core machine learning algorithm used in recommender systems and other domains with missing data. While the matrix case is well-understood, theoretical result…
BrainViewer: interacting with spatial connectome data at the mesoscale
Seth Daetwiler, Angus Read, Jessica Stillwell +1
Scientists construct connectomes, comprehensive descriptions of neuronal connections across a brain, in order to better understand and model brain function. Interactive visualizati…
Deterministic tensor completion with hypergraph expanders
Kameron Decker Harris, Yizhe Zhu
We provide a novel analysis of low-rank tensor completion based on hypergraph expanders. As a proxy for rank, we minimize the max-quasinorm of the tensor, which generalizes the max…
Additive function approximation in the brain
Kameron Decker Harris
Many biological learning systems such as the mushroom body, hippocampus, and cerebellum are built from sparsely connected networks of neurons. For a new understanding of such netwo…
Centering Data Improves the Dynamic Mode Decomposition
Seth M. Hirsh, Kameron Decker Harris, J. Nathan Kutz +1
Dynamic mode decomposition (DMD) is a data-driven method that models high-dimensional time series as a sum of spatiotemporal modes, where the temporal modes are constrained by line…
Time-varying Autoregression with Low Rank Tensors
Kameron Decker Harris, Aleksandr Aravkin, Rajesh Rao +1
We present a windowed technique to learn parsimonious time-varying autoregressive models from multivariate timeseries. This unsupervised method uncovers interpretable spatiotempora…
Greedy low-rank algorithm for spatial connectome regression
Patrick Kürschner, Sergey Dolgov, Kameron Decker Harris +1
Recovering brain connectivity from tract tracing data is an important computational problem in the neurosciences. Mesoscopic connectome reconstruction was previously formulated as…
Spectral gap in random bipartite biregular graphs and applications
Gerandy Brito, Ioana Dumitriu, Kameron Decker Harris
We prove an analogue of Alon's spectral gap conjecture for random bipartite, biregular graphs. We use the Ihara-Bass formula to connect the non-backtracking spectrum to that of the…
Different roles for inhibition in the rhythm-generating respiratory network
Kameron Decker Harris, Tatiana Dashevskiy, Joshua Mendoza +3
Unraveling the interplay of excitation and inhibition within rhythm-generating networks remains a fundamental issue in neuroscience. We use a biophysical model to investigate the d…
High resolution neural connectivity from incomplete tracing data using nonnegative spline regression
Kameron Decker Harris, Stefan Mihalas, Eric Shea-Brown
Whole-brain neural connectivity data are now available from viral tracing experiments, which reveal the connections between a source injection site and elsewhere in the brain. Thes…
Reply to Garcia et al.: Common mistakes in measuring frequency dependent word characteristics
P. S. Dodds, E. M. Clark, S. Desu +11
We demonstrate that the concerns expressed by Garcia et al. are misplaced, due to (1) a misreading of our findings in [1]; (2) a widespread failure to examine and present words in…
Human language reveals a universal positivity bias
Peter Sheridan Dodds, Eric M. Clark, Suma Desu +11
Using human evaluation of 100,000 words spread across 24 corpora in 10 languages diverse in origin and culture, we present evidence of a deep imprint of human sociality in language…
Dynamical influence processes on networks: General theory and applications to social contagion
Kameron Decker Harris, Christopher M. Danforth, Peter Sheridan Dodds
We study binary state dynamics on a network where each node acts in response to the average state of its neighborhood. Allowing varying amounts of stochasticity in both the network…
The Geography of Happiness: Connecting Twitter sentiment and expression, demographics, and objective characteristics of place
Lewis Mitchell, Kameron Decker Harris, Morgan R. Frank +2
We conduct a detailed investigation of correlations between real-time expressions of individuals made across the United States and a wide range of emotional, geographic, demographi…
On-off Threshold Models of Social Contagion
Kameron Decker Harris
We study binary state contagion dynamics on a social network where nodes act in response to the average state of their neighborhood. We model the competing tendencies of imitation…
Limited Imitation Contagion on Random Networks: Chaos, Universality, and Unpredictability
Peter Sheridan Dodds, Kameron Decker Harris, Christopher M. Danforth
We study a family of binary state, socially-inspired contagion models which incorporate imitation limited by an aversion to complete conformity. We uncover rich behavior in our mod…
Twitter reciprocal reply networks exhibit assortativity with respect to happiness
Catherine A. Bliss, Isabel M. Kloumann, Kameron Decker Harris +2
The advent of social media has provided an extraordinary, if imperfect, 'big data' window into the form and evolution of social networks. Based on nearly 40 million message pairs p…
Predicting flow reversals in chaotic natural convection using data assimilation
Kameron Decker Harris, El Hassan Ridouane, Darren L. Hitt +1
A simplified model of natural convection, similar to the Lorenz (1963) system, is compared to computational fluid dynamics simulations in order to test data assimilation methods an…
Direct, physically motivated derivation of triggering probabilities for spreading processes on generalized random networks
Kameron Decker Harris, Joshua L. Payne, Peter Sheridan Dodds
We derive a general expression for the probability of global spreading starting from a single infected seed for contagion processes acting on generalized, correlated random network…
Positivity of the English language
Isabel M. Kloumann, Christopher M. Danforth, Kameron Decker Harris +2
Over the last million years, human language has emerged and evolved as a fundamental instrument of social communication and semiotic representation. People use language in part to…
Empirical correction of a toy climate model
Nicholas A. Allgaier, Kameron D. Harris, Christopher M. Danforth
Improving the accuracy of forecast models for physical systems such as the atmosphere is a crucial ongoing effort. Errors in state estimation for these often highly nonlinear syste…
Exact solutions for social and biological contagion models on mixed directed and undirected, degree-correlated random networks
Joshua L. Payne, Kameron Decker Harris, Peter Sheridan Dodds
We derive analytic expressions for the possibility, probability, and expected size of global spreading events starting from a single infected seed for a broad collection of contagi…
Direct, physically-motivated derivation of the contagion condition for spreading processes on generalized random networks
Peter Sheridan Dodds, Kameron Decker Harris, Joshua L. Payne
For a broad range single-seed contagion processes acting on generalized random networks, we derive a unifying analytic expression for the possibility of global spreading events in…