BIs vitenskapelige produksjon er registrert i den nasjonale databasen Cristin (Current Research Information System In Norway).
Forskning og faglige
Institutt for datavitenskap og analyse
Institutt for datavitenskap og analyse er det niende instituttet på BI, og det ble etablert i 2020. Våre forskere har bakgrunn fra statistikk, maskinlæring, statistisk læring og/eller kunstig intelligens.
Publikasjoner
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A flexible predictive density combination for large financial data sets in regular and crisis periods
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COCO: an annotated Twitter dataset of COVID-19 conspiracy theories
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Optimizing insect metabarcoding using replicated mock communities
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Partial Identification of Latent Correlations with Ordinal Data
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Nowcasting industrial production using linear and non-linear models of electricity demand
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Forecasting consumer confidence through semantic network analysis of online news
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Persistence Initialization: a novel adaptation of the Transformer architecture for time series forecasting
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Vector Quantized Time Series Generation with a Bidirectional Prior ModelProceedings of Machine Learning Research (PMLR), 206, p. 7665-7693.
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Incorporating air temperature into mid-term electricity load forecasting models using time-series regressions and neural networks
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The COVID-19 pandemic and family business performance
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Forecasting regional GDPs: a comparison with spatial dynamic panel data models
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Are low frequency macroeconomic variables important for high frequency electricity prices?
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Macroeconomic uncertainty and bank lendingVis sammendrag
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A Bayesian DSGE approach to modelling cryptocurrency
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Constructing a Knowledge Graph from Textual Descriptions of Software Vulnerabilities in the National Vulnerability Database
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Measuring Agreement Using Guessing Models and Knowledge Coefficients
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Proper Scoring Rules for Evaluating Density Forecasts with Asymmetric Loss Functions
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Short-term hydropower optimization driven by innovative time-adapting econometric model
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Infinite diameter confidence sets in Hedges’ publication bias model
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Forecasting financial markets with semantic network analysis in the COVID-19 crisis
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SOLBP: Second-Order Loopy Belief Propagation for Inference in Uncertain Bayesian Networks
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Forecasting electricity prices with expert, linear, and nonlinear models
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Compiling Universal Probabilistic Programming Languages with Efficient Parallel Sequential Monte Carlo Inference
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COVID-19 and 5G conspiracy theories: long term observation of a digital wildfire
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Probabilistic Judgement Aggregation by Opinion Update
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Incremental Clustering Algorithms for Massive Dynamic GraphsVis sammendrag
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A Streaming System for Large-scale Temporal Graph Mining of Reddit Data
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Generating customer's credit behavior with deep generative models
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Impacts of Covid-19 on Norwegian salmon exports: A firm-level analysis
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An interpretable unsupervised Bayesian network model for fault detection and diagnosis
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Large Time-Varying Volatility Models for Hourly Electricity Prices*
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A multivariate dependence analysis for electricity prices, demand and renewable energy sources
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A CLT FOR SECOND DIFFERENCE ESTIMATORS WITH AN APPLICATION TO VOLATILITY AND INTENSITY
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Markov switching panel with endogenous synchronization effects
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Forecasting energy commodity prices: A large global dataset sparse approach
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Contagion between real estate and financial markets: A Bayesian quantile-on-quantile approach
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The partly parametric and partly nonparametric additive risk model
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A new decision making model based on Rank Centrality for GDM with fuzzy preference relations
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iPUG for Multiple Graphcore IPUs: Optimizing Performance and Scalability of Parallel Breadth-First Search
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iPUG: Accelerating Breadth-First Graph Traversals Using Manycore Graphcore IPUs
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World steel production: A new monthly indicator of global real economic activity
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Time is of the essence: A joint Hierarchical RNN and Point Process model for time and item predictions
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Virtual metrology modeling based on gaussian bayesian network
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Bayesian Nonparametric Calibration and Combination of Predictive Distributions
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Macroeconomic Forecasting Performance under Alternative Specifications of Time-Varying Volatility