相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。ChemML: A machine learning and informatics program package for the analysis, mining, and modeling of chemical and materials data
Mojtaba Haghighatlari et al.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE (2020)
Evaluating Scalable Uncertainty Estimation Methods for Deep Learning-Based Molecular Property Prediction
Gabriele Scalia et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2020)
Comprehensive Analysis of Applicability Domains of QSPR Models for Chemical Reactions
Assima Rakhimbekova et al.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES (2020)
Uncertainty Quantification Using Neural Networks for Molecular Property Prediction
Lior Hirschfeld et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2020)
The Real-World-Weight Cross-Entropy Loss Function: Modeling the Costs of Mislabeling
Yaoshiang Ho et al.
IEEE ACCESS (2020)
Accelerated Discovery of High-Refractive-Index Polyimides via First-Principles Molecular Modeling, Virtual High-Throughput Screening, and Data Mining
Mohammad Atif Faiz Afzal et al.
JOURNAL OF PHYSICAL CHEMISTRY C (2019)
Advances of machine learning in molecular modeling and simulation
Mojtaba Haghighatlari et al.
CURRENT OPINION IN CHEMICAL ENGINEERING (2019)
Molecular Similarity-Based Domain Applicability Metric Efficiently Identifies Out-of-Domain Compounds
Ruifeng Liu et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2019)
Fast and Accurate Uncertainty Estimation in Chemical Machine Learning
Felix Musil et al.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION (2019)
A deep neural network model for packing density predictions and its application in the study of 1.5 million organic molecules
Mohammad Atif Faiz Afzal et al.
CHEMICAL SCIENCE (2019)
A quantitative uncertainty metric controls error in neural network-driven chemical discovery
Jon Paul Janet et al.
CHEMICAL SCIENCE (2019)
Combining first-principles and data modeling for the accurate prediction of the refractive index of organic polymers
Mohammad Atif Faiz Afzal et al.
JOURNAL OF CHEMICAL PHYSICS (2018)
Building and deploying a cyberinfrastructure for the data-driven design of chemical systems and the exploration of chemical space
Johannes Hachmann et al.
MOLECULAR SIMULATION (2018)
Analysis of the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE) in Assessing Rounding Model
Weijie Wang et al.
2017 5TH INTERNATIONAL CONFERENCE ON MECHANICAL ENGINEERING, MATERIALS SCIENCE AND CIVIL ENGINEERING (2018)
Addressing uncertainty in atomistic machine learning
Andrew A. Peterson et al.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS (2017)
Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations?
David Bajusz et al.
JOURNAL OF CHEMINFORMATICS (2015)
The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets
Takaya Saito et al.
PLOS ONE (2015)
Assessment of Machine Learning Reliability Methods for Quantifying the Applicability Domain of QSAR Regression Models
Marko Toplak et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2014)
Root mean square error (RMSE) or mean absolute error (MAE)? - Arguments against avoiding RMSE in the literature
T. Chai et al.
GEOSCIENTIFIC MODEL DEVELOPMENT (2014)
Open Babel: An open chemical toolbox
Noel M. O'Boyle et al.
JOURNAL OF CHEMINFORMATICS (2011)
MAPE-R: a rescaled measure of accuracy for cross-sectional subnational population forecasts
David A. Swanson et al.
JOURNAL OF POPULATION RESEARCH (2011)
Extended-Connectivity Fingerprints
David Rogers et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2010)
Applicability of the Revised Mean Absolute Percentage Errors (MAPE) Approach to Some Popular Normal and Non-normal Independent Time Series
Louie Ren et al.
INTERNATIONAL ADVANCES IN ECONOMIC RESEARCH (2009)
Comparison of approaches for estimating reliability of individual regression predictions
Zoran Bosnic et al.
DATA & KNOWLEDGE ENGINEERING (2008)
Cost curves: An improved method for visualizing classifier performance
Chris Drummond et al.
MACHINE LEARNING (2006)
On the use of dimensioned measures of error to evaluate the performance of spatial interpolators
CJ Willmott et al.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE (2006)
An introduction to ROC analysis
Tom Fawcett
PATTERN RECOGNITION LETTERS (2006)
Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance
CJ Willmott et al.
CLIMATE RESEARCH (2005)
Coevolutionary free lunches
DH Wolpert et al.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2005)
QSAR applicability domain estimation by projection of the training set in descriptor space: A review
J Jaworska et al.
ATLA-ALTERNATIVES TO LABORATORY ANIMALS (2005)
The accuracy of intermittent demand estimates
AA Syntetos et al.
INTERNATIONAL JOURNAL OF FORECASTING (2005)
Using AUC and accuracy in evaluating learning algorithms
J Huang et al.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2005)
Reoptimization of MDL keys for use in drug discovery
JL Durant et al.
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES (2002)
A simple generalisation of the area under the ROC curve for multiple class classification problems
DJ Hand et al.
MACHINE LEARNING (2001)
分享论文
