Skip to main navigation
Skip to search
Skip to main content
National Laboratory of the Rockies Hub Home
Search content at National Laboratory of the Rockies
Hub Home
Researcher Profiles
Research Output
Research Organizations
Awards & Honors
Activities
Predicting Li-Ion Battery Capacity Fade Using Early-Life Data and a Hybrid Data-Driven Gaussian Process-Bayesian Regression Approach
Kinshuk Panda
,
Malik Hassanaly
, Nina Prakash
,
Paul Gasper
,
Peter Weddle
,
Katharine Harrison
Computational Science
Center for Energy Conversion and Storage Systems
Materials Science
Research output
:
NLR
›
Presentation
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Predicting Li-Ion Battery Capacity Fade Using Early-Life Data and a Hybrid Data-Driven Gaussian Process-Bayesian Regression Approach'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Mathematics
Bayesian
100%
Gaussian Process
100%
Functional Form
62%
Data Point
37%
Power Law
25%
Mixture Model
25%
Life Cycle
25%
Confidence Interval
12%
Posterior Distribution
12%
Regression Model
12%
Observation Data
12%
Accurate Prediction
12%
Parameter Distribution
12%
Epistemic Uncertainty
12%
Computer Science
Functional Form
100%
Prediction Accuracy
40%
Data Capacity
40%
Open Source
20%
Sigmoidal Function
20%
Posterior Distribution
20%
Performance Trade
20%