Probable networks and plausible predictions — a review of practical Bayesian methods for supervised neural networks

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High Throughput Screening of Millions of van der Waals Heterostructures for Superlubricant Applications

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Variational Approach to Factor Analysis and Related Models

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Supervised classification with structured class definitions

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Augmenting the Softmax with Additional Confidence Scores for Improved Selective Classification with Out-of-Distribution Data

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Bayesian Calibration of Car-Following Models

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Short-Term Power Load Forecasting Using Least Squares Support Vector Machines(LS-SVM)

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Vented gas explosion overpressure prediction of obstructed cubic chamber by Bayesian Regularization Artificial Neuron Network – Bauwens model

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An integrated Bayesian least-squares-support-vector-machine factorial-analysis (B-LSVM-FA) method for inferring inflow from the Amu Darya to the Aral Sea under ensemble prediction

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Bayesian Hyperparameter Optimization of Deep Neural Network Algorithms Based on Ant Colony Optimization

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An application of methods for the probabilistic three-class classification of pregnancies of unknown location

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Incremental and online learning through extended kalman filtering with constraint weights for freeway travel time prediction

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Continuous optimization of hyper-parameters

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Accelerated learning using Gaussian process models to predict static recrystallization in an Al-Mg alloy

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Modelling microstructural evolution during annealing

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Sampling-Free Variational Inference of Bayesian Neural Networks by Variance BackpropagationPreprint

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HyperEDL: Spectral-Spatial Evidence Deep Learning for Cross-Scene Hyperspectral Image Classification

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How can we quantify, explain, and apply the uncertainty of complex soil maps predicted with neural networks?

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Physics-Constrained, Data-Driven Discovery of Coarse-Grained Dynamics

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Uncertainty quantification and reliability analysis by an adaptive sparse Bayesian inference based PCE model

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Periodic nonlinear principal component neural networks for humanoid motion segmentation, generalization, and generation

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Analysis of Pesticide Mixtures Using Intelligent Biosensors

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Strain induced transformation of retained austenite in TRIP aided steels: A neural network model

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Family Discovery

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Bayesian methods for Support Vector machines and Gaussian processes

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Machine Learning Methods in Site‐Specific Management Research: An Australian Case Study

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Bayesian Convolutional Neural NetworksPreprint

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Dangers of Bayesian Model Averaging under Covariate ShiftPreprint

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Seeking new physics in cosmology with Bayesian neural networks: Dark energy and modified gravity

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Safety Monitoring of Neural Networks Using Unsupervised Feature Learning and Novelty Estimation

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Performance versus resilience in modern quark-gluon tagging

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Application of artificial neural network to fMRI regression analysis

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Non-informative hierarchical Bayesian inference for non-negative matrix factorization

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Bayesian sparse reconstruction: a brute-force approach to astronomical imaging and machine learning

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Tools to reverse-engineer multicellular systems: case studies using the fruit fly

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Analysis of Damage Accumulations in High Strength Low Alloy Steels under Monotonic Deformation

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Model-Based Design Analysis and Yield Optimization

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Infinite models for speaker clustering

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The Method of Oilfield Development Risk Forecasting and Early Warning Using Revised Bayesian Network

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Non-linear Methods for the Analysis of Metabolic Profiles

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Modeling of mechanical properties in alpha/beta-titanium alloys

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Object Recognition via Local Patch Labelling

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Data Mining in Materials Development

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Variational Bayesian Adaptation for Speaker Clustering

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A hierarchical Bayesian model to find brain-behaviour associations in incomplete data sets

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Chemometrics Approach Based on Wavelet Transforms for the Estimation of Monomer Concentrations from FTIR Spectra

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A framework for strategic discovery of credible neural network surrogate models under uncertainty

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Laplace Group Sensing for Acoustic Models

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Detecting regulatory gene–environment interactions with unmeasured environmental factors

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Calculation of Crystallographic Texture of BCC Steels During Cold Rolling

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A Bayesian Machine Learning Algorithm for Predicting ENSO Using Short Observational Time Series

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Online AMR Domestic Load Profile Characteristic Change Monitor to Support Ancillary Demand Services

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Classifying ovarian tumors using Bayesian Multi-Layer Perceptrons and Automatic Relevance Determination: A multi-center study

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Comparison of the LS-SVM based load forecasting models

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A Bayesian nonlinear support vector machine error correction model

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Bayesian Methods for fMRI Time-Series Analysis Using a Nonstationary Model for the Noise

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A Bayesian approach to object detection using probabilistic appearance-based models

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Rule extraction by successive regularization

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Gaussian Processes for Regression and Optimisation

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Now What Sequence? Pre-trained Ensembles for Bayesian Optimization of Protein SequencesPreprint

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Smart Experience and Green Health Tourism: The Moderating Role of Content Marketing

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Test-retest reliability of high angular resolution diffusion imaging acquisition within medial temporal lobe connections assessed via tract based spatial statistics, probabilistic tractography and a novel graph theory metric

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Itakura-Saito Nonnegative Factorizations of the Power Spectrogram for Music Signal Decomposition

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A deep hypersphere approach to high-dimensional anomaly detection

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The Relevance Vector Machine Applied to the Modeling of Wireless Channels

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Construction and Methods of Learning of Bayesian Networks

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Automatic Rank Determination in Projective Nonnegative Matrix Factorization

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Machine-learning in astronomy

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A Variational Bayesian Causal Analysis Approach for Time-Varying Systems

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Prediction of the Atomization Energy of Molecules Using Coulomb Matrix and Atomic Composition in a Bayesian Regularized Neural Networks

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RECONSTRUCTING GENETIC NETWORKS FROM TIME ORDERED GENE EXPRESSION DATA USING BAYESIAN METHOD WITH GLOBAL SEARCH ALGORITHM

Wang, S.-C. (2004) · Journal of Bioinformatics and Computational Biology · doi:10.1142/s0219720004000673 · Cited by 13

Bayesian Convolutional Neural Networks with Variational InferencePreprint

Shridhar, K., Laumann, F., Maurin, A. L., Olsen, M. A., & Liwicki, M. (2018) · arXiv (Cornell University) · Cited by 15

Fast Predictive Uncertainty for Classification with Bayesian Deep NetworksPreprint

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Probing as Quantifying Inductive Bias

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Towards a data-driven model of hadronization using normalizing flows

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Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums

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Bayesian neuroevolution using distributed swarm optimization and tempered MCMC

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Physically Constrained Neural Network Models for Simulation

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Mechanical properties of a high-strength cupronickel alloy-Bayesian neural network analysis

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Geometric Mistuning Reduced-Order Model Development Utilizing Bayesian Surrogate Models for Component Mode Calculations

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Evidential Reasoning and Learning: a Survey

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Evolutionary Sound Matching: A Test Methodology and Comparative Study

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Time-Series Interval Forecasting with Dual-Output Monte Carlo Dropout: A Case Study on Durian Exports

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Bayesian neural network enhancing reliability against conductance drift for memristor neural networks

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Machine learning synthetic spectra for probabilistic redshift estimation: SYTH-Z

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Spatio-temporal reconstruction of brain dynamics from EEG with a Markov prior

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Machine Learning the Sixth Dimension: Stellar Radial Velocities from 5D Phase-space Correlations

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A low-cost variational-Bayes technique for merging mixtures of probabilistic principal component analyzers

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Using Bayesian neural networks with ARD input selection to detect malignant ovarian masses prior to surgery

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A neural network model for dose–response of foodborne pathogens

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Identifying Functional Binding Motifs of Tumor Protein p53 Using Support Vector Machines

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Short-term traffic flow forecasting based on clustering and feature selection

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Bayesian Quantification of Contrast-Enhanced Ultrasound Images With Adaptive Inclusion of an Irreversible Component

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The Performance of LVQ Based Automatic Relevance Determination Applied to Spontaneous Biosignals

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Pattern recognition and machine learning for magnetic resonance images with kernel methods

Chu, C. (2009) · UCL Discovery (University College London) · Cited by 10

Cold Posteriors and Aleatoric UncertaintyPreprint

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Analysis of a Gaussian process and feed-forward neural networks based filter for forecasting short rainfall time series

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Grounding Bayesian accounts of numerosity and variability effects in a similarity-based framework: the case of self-organising maps

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Benchmarking Scalable Predictive Uncertainty in Text Classification

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Siamese Convolutional Neural Networks to Quantify Crack Pattern Similarity in Masonry Facades

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New statistical model for radar HRRP target recognition

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Bayesian Methods for Backpropagation Networks

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