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Journal of the American Statistical Association, ISSN 0162-1459, 01/2018, Volume 113, Issue 521, pp. 269 - 279
Many practical problems are related to prediction, where the main interest is at subject (e.g., personalized medicine) or (small) sub-population (e.g., small... 
Mean squared prediction error | Linear mixed model | Mixed effects | CMMP | Future observation | Prediction interval | TRAJECTORIES | SMALL-AREA ESTIMATION | STATISTICS & PROBABILITY | ERROR | CONDITIONAL INFERENCE | Training
Journal Article
Journal Article
IEEE Transactions on Software Engineering, ISSN 0098-5589, 01/2017, Volume 43, Issue 1, pp. 1 - 18
Journal Article
Nature Neuroscience, ISSN 1097-6256, 04/2015, Volume 18, Issue 5, pp. 767 - 772
Journal Article
International Journal of Adaptive Control and Signal Processing, ISSN 0890-6327, 12/2017, Volume 31, Issue 12, pp. 1853 - 1870
Journal Article
68. A quantitative uncertainty metric controls error in neural network-driven chemical discovery (Electronic supplementary information (ESI) available: Information about ensembles and mc-dropout procedure, information about DFT methods, information about training ligands and structures, information about CSD test cases, PCA decay plots and model performance information for inorganic dataset, comparison between single ANN and ensemble predictions and distribution of CSD errors, error distributions with different distance metrics and numbers of neighbors, correlation between errors and uncertainty metrics, maximum and average retained inorganic errors as function of uncertain metrics, CSD codes used to calibrate latent distance model, variation in uncertainty model calibration parameters for CSD data, type I error rates and with retained errors, architecture and hyperparameters used for QM9 prediction task, performance results for different architectures on QM9 prediction task, variation in QM9 performance with test/train split, performance and error distribution for QM9 for single ANN and ensembles, correlation between QM9 errors and uncertainty metrics, retained mean QM9 errors with different uncertainty metrics, variation in uncertainty model calibration parameters for QM9 data, distribution of predicted and actual errors for QM9 data, results of active learning experiment, hyperparameters for inorganic ANN (PDF). Summary DFT results and information for training and CSD data; model predictions, errors and uncertainties for all tests; DFT-optimized geometries of training and CSD data; model weights, architectures and scaling data for inorganic and QM9 ANNs (ZIP). See DOI: 10.1039/c9sc02298h)
Chemical Science, ISSN 2041-6520, 01/2019, Volume 10, Issue 34, pp. 7913 - 7922
Machine learning (ML) models, such as artificial neural networks, have emerged as a complement to high-throughput screening, enabling characterization of new... 
Data points | Active learning | Artificial neural networks | Calibration | Learning theory | Training | Organic chemistry | Errors | Neural networks | Parameter uncertainty | Machine learning | Predictions | Cutoffs | Mathematical models | Space exploration | Predictive control
Journal Article
Journal of the American Statistical Association, ISSN 0162-1459, 07/2014, Volume 109, Issue 507, pp. 991 - 1007
Journal Article
Global Ecology and Biogeography, ISSN 1466-822X, 2/2013, Volume 22, Issue 1/2, pp. 252 - 260
Journal Article
Current Opinion in Neurobiology, ISSN 0959-4388, 04/2018, Volume 49, pp. 1 - 7
Phasic dopamine responses are thought to encode a prediction-error signal consistent with model-free reinforcement learning theories. However, a number of... 
NEURONS ENCODE | RESPONSES | DECISIONS | ERRORS | MULTIDIMENSIONAL ENVIRONMENTS | CHOLINERGIC INTERNEURONS | REPRESENTATION | REWARD-PREDICTION | MECHANISMS | ORBITOFRONTAL CORTEX | NEUROSCIENCES | Learning - physiology | Animals | Dopamine - physiology | Computer Simulation | Humans | Reinforcement, Psychology | Models, Neurological | Phenols | Models | Dopamine | Analysis
Journal Article
74.