Concepedia

Author

Bhavya Kailkhura

Lawrence Livermore National LaboratoryORCID

Also Known As

B Kailkhura, B. Kailkhura, Ben-Nun, Tal, Bhavya Kailkhura, Bhavya, Kailkhura, Ferdinando Fioretto, Fioretto, Ferdinando, K.Bhavya ., Kailkhura Bhavya, Kailkhura, Bhavya

235

Publications

2.9K

Citations

27

H-Index

152

Concepts

All Affiliations

Lawrence Livermore National LaboratorySyracuse University
BK

About

Bhavya Kailkhura is an author at Lawrence Livermore National Laboratory specializing in computer science, engineering, and data science.

Top Concepts

#ConceptH-IndexPublicationsCitations

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Engineering

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Business

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Health Sciences

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Language Studies

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Management

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27

Bhavya Kailkhura

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60

Publications

2.4K

Citations

27

H-Index

YearCitations

Explainable machine learning in materials science

Xiaoting Zhong, Brian Gallagher, Shusen Liu,

npj Computational Materials

2022

302

Anomalous Example Detection in Deep Learning: A Survey

Saikiran Bulusu, Bhavya Kailkhura, Bo Li,

IEEE Access

2020

175

A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning: Principals, Recent Advances, and Applications

Sijia Liu, Pin‐Yu Chen, Bhavya Kailkhura,

IEEE Signal Processing Magazine

2020

161

Distributed Bayesian Detection in the Presence of Byzantine Data

Bhavya Kailkhura, Yunghsiang S. Han, Swastik Brahma,

IEEE Transactions on Signal Processing

2015

108

Automatic Perturbation Analysis for Scalable Certified Robustness and Beyond

Kaidi Xu, Zhouxing Shi, Huan Zhang,

arXiv (Cornell University)

2020

92

Data Falsification Attacks on Consensus-Based Detection Systems

Bhavya Kailkhura, Swastik Brahma, Pramod K. Varshney

IEEE Transactions on Signal and Information Processing over Networks

2016

79

Generative Counterfactual Introspection for Explainable Deep Learning

Shusen Liu, Bhavya Kailkhura, Donald Loveland,

2019

74

Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization

Sijia Liu, Bhavya Kailkhura, Pin‐Yu Chen,

OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information)

2018

71

Nanomaterial Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge

Anna M. Hiszpanski, Brian Gallagher, Karthik Chellappan,

Journal of Chemical Information and Modeling

2020

62

On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method

Pu Zhao, Sijia Liu, Pin‐Yu Chen,

2019

58

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