Brian Gallagher - Publications, H-index & Citations

Brian Gallagher

Lawrence Livermore National Laboratory

34H指数

217论文数

9.7K被引数

收录论文 18

发表时间

A comparative study of predicting high entropy alloy phase fractions with traditional machine learning and deep neural networks 传统机器学习和深度神经网络预测高熵合金相分数的对比研究

NPJ COMPUTATIONAL MATERIALS

IF11.9

2024-08-09

OAAI

Liu, Shusen; Bocklund, Brandon; Diffenderfer, James; Chaganti, Shreya; Kailkhura, Bhavya; McCall, Scott K.; Gallagher, Brian; Perron, Aurelien; McKeown, Joseph T.

Explainable machine learning in materials science 材料科学中的可解释机器学习

NPJ COMPUTATIONAL MATERIALS

IF11.9

2022-09-22

121

OAAI

Zhong, Xiaoting; Gallagher, Brian; Liu, Shusen; Kailkhura, Bhavya; Hiszpanski, Anna; Han, T. Yong-Jin

A Strategic Approach to Machine Learning for Material Science: How to Tackle Real-World Challenges and Avoid Pitfalls

CHEMISTRY OF MATERIALS

IF7

2022-09-01

OAAI

Karande, Piyush; Gallagher, Brian; Han, Thomas Yong-Jin

Accurate parameterization of the kinetic energy functional 动能泛函的精确参数化

JOURNAL OF CHEMICAL PHYSICS

IF3.1

2022-01-13

OAAI

Kumar, Shashikant; Borda, Edgar Landinez; Sadigh, Babak; Zhu, Siya; Hamel, Sebastian; Gallagher, Brian; Bulatov, Vasily; Klepeis, John; Samanta, Amit

Accurate parameterization of the kinetic energy functional for calculations using exact-exchange 使用精确交换进行计算的动能函数的精确参数化

JOURNAL OF CHEMICAL PHYSICS

IF3.1

2022-01-11

OAAI

Kumar, Shashikant; Sadigh, Babak; Zhu, Siya; Suryanarayana, Phanish; Hamel, Sebastian; Gallagher, Brian; Bulatov, Vasily; Klepeis, John; Samanta, Amit

A study of real-world micrograph data quality and machine learning model robustness

NPJ COMPUTATIONAL MATERIALS

IF11.9

2021-10-05

OAAI

Zhong, Xiaoting; Gallagher, Brian; Eves, Keenan; Robertson, Emily; Mundhenk, T. Nathan; Han, T. Yong-Jin

Predicting compressive strength of consolidated molecular solids using computer vision and deep learning

MATERIALS & DESIGN

IF7.9

2020-05-01

OAAI

Gallagher, Brian; Rever, Matthew; Loveland, Donald; Mundhenk, T. Nathan; Beauchamp, Brock; Robertson, Emily; Jaman, Golam G.; Hiszpanski, Anna M.; Han, T. Yong-Jin

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

JOURNAL OF CHEMICAL INFORMATION AND MODELING

IF5.3

2020-04-14

OAAI

Hiszpanski, Anna M.; Gallagher, Brian; Chellappan, Karthik; Li, Peggy; Liu, Shusen; Kim, Hyojin; Han, Jinkyu; Kailkhura, Bhavya; Buttler, David J.; Han, Thomas Yong-Jin

Reliable and explainable machine-learning methods for accelerated material discovery 用于加速材料发现的可靠且可解释的机器学习方法

NPJ COMPUTATIONAL MATERIALS

IF11.9

2019-11-14

123

OAAI

Kailkhura, Bhavya; Gallagher, Brian; Kim, Sookyung; Hiszpanski, Anna; Han, T. Yong-Jin

Network Structure Inference, A Survey: Motivations, Methods, and Applications

ACM COMPUTING SURVEYS

IF28

2018-04-17

OAAI