20 citations · 41 across the 10 of their papers we have counts for
10 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…
Gaussian Partial Information Decomposition: Bias Correction and Application to High-dimensional Data
Praveen Venkatesh, Corbett Bennett, Sam Gale +5
Recent advances in neuroscientific experimental techniques have enabled us to simultaneously record the activity of thousands of neurons across multiple brain regions. This has led…
Capturing and Interpreting Unique Information
Praveen Venkatesh, Keerthana Gurushankar, Gabriel Schamberg
Partial information decompositions (PIDs), which quantify information interactions between three or more variables in terms of uniqueness, redundancy and synergy, are gaining tract…
Extracting Unique Information Through Markov Relations
Keerthana Gurushankar, Praveen Venkatesh, Pulkit Grover
We propose two new measures for extracting the unique information in and not about a message , when and are joint random variables with a given joint distribu…
Quantifying Feature Contributions to Overall Disparity Using Information Theory
Sanghamitra Dutta, Praveen Venkatesh, Pulkit Grover
When a machine-learning algorithm makes biased decisions, it can be helpful to understand the sources of disparity to explain why the bias exists. Towards this, we examine the prob…
Can Information Flows Suggest Targets for Interventions in Neural Circuits?
Praveen Venkatesh, Sanghamitra Dutta, Neil Mehta +1
Motivated by neuroscientific and clinical applications, we empirically examine whether observational measures of information flow can suggest interventions. We do so by performing…
Partial Information Decomposition via Deficiency for Multivariate Gaussians
Praveen Venkatesh, Gabriel Schamberg
Bivariate partial information decompositions (PIDs) characterize how the information in a "message" random variable is decomposed between two "constituent" random variables in term…
Fairness Under Feature Exemptions: Counterfactual and Observational Measures
Sanghamitra Dutta, Praveen Venkatesh, Piotr Mardziel +2
With the growing use of ML in highly consequential domains, quantifying disparity with respect to protected attributes, e.g., gender, race, etc., is important. While quantifying di…
Information Flow in Computational Systems
Praveen Venkatesh, Sanghamitra Dutta, Pulkit Grover
We develop a theoretical framework for defining and identifying flows of information in computational systems. Here, a computational system is assumed to be a directed graph, with…
Testing Changes in Communities for the Stochastic Block Model
Aditya Gangrade, Praveen Venkatesh, Bobak Nazer +1
We propose and analyze the problems of \textit{community goodness-of-fit and two-sample testing} for stochastic block models (SBM), where changes arise due to modification in commu…