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of 235
pro vyhledávání: '"Grover, Pulkit"'
Quantifying relevant interactions between neural populations is a prominent question in the analysis of high-dimensional neural recordings. However, existing dimension reduction methods often discuss communication in the absence of a formal framework
Externí odkaz:
http://arxiv.org/abs/2407.02450
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, redundant, and synergistic terms. Recently, PID has shown promise as an eme
Externí odkaz:
http://arxiv.org/abs/2305.07013
Autor:
Goswami, Chaitanya, Grover, Pulkit
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. Traditionally, the design of such stimuli has been model-driven. Due to c
Externí odkaz:
http://arxiv.org/abs/2211.10823
Publikováno v:
2022 58th Annual Allerton Conference on Communication, Control, and Computing (Allerton)
We propose two new measures for extracting the unique information in $X$ and not $Y$ about a message $M$, when $X, Y$ and $M$ are joint random variables with a given joint distribution. We take a Markov based approach, motivated by questions in fair
Externí odkaz:
http://arxiv.org/abs/2210.14789
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 problem of quantifying the contribution of each individual feature to the
Externí odkaz:
http://arxiv.org/abs/2206.08454
Publikováno v:
Advances in Neural Information Processing Systems 34 (NeurIPS 2021)
Motivated by neuroscientific and clinical applications, we empirically examine whether observational measures of information flow can suggest interventions. We do so by performing experiments on artificial neural networks in the context of fairness i
Externí odkaz:
http://arxiv.org/abs/2111.05299
Autor:
Gurushankar, Keerthana, Grover, Pulkit
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 influential paper of Jonas and Kording, that examines a microprocessor
Externí odkaz:
http://arxiv.org/abs/2110.00889
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 disparity is essential, sometimes the needs of an occupation may require
Externí odkaz:
http://arxiv.org/abs/2006.07986
Akademický článek
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Publikováno v:
In Journal of Theoretical Biology 7 September 2023 572
