803 citations · 1.1k across the 37 of their papers we have counts for
40 papers
Computing Unique Information for Poisson and Multinomial Systems
Chaitanya Goswami, Amanda Merkley, Pulkit Grover
Bivariate Partial Information Decomposition (PID) describes how the mutual information between a random variable M and two random variables Y and Z is decomposed into unique, redun…
PATHFINDER: Designing Stimuli for Neuromodulation through data-driven inverse estimation of non-linear functions
Chaitanya Goswami, Pulkit Grover
There has been tremendous interest in designing stimuli (e.g. electrical currents) that produce desired neural responses, e.g., for inducing therapeutic effects for treatments. Tra…
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…
A Minimal Intervention Definition of Reverse Engineering a Neural Circuit
Keerthana Gurushankar, Pulkit Grover
In neuroscience, researchers have developed informal notions of what it means to reverse engineer a system, e.g., being able to model or simulate a system in some sense. A recent i…