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Found 10 papers, 1 papers with code
Bayesian Estimation of Panel Models under Potentially Sparse Heterogeneity
We incorporate a version of a spike and slab prior, comprising a pointmass at zero ("spike") and a Normal distribution around zero ("slab") into a dynamic panel data framework to model coefficient heterogeneity.
HybridCVLNet: A Hybrid CSI Feedback System and its Domain Adaptation
Deep Learning (DL)-based channel state information (CSI) feedback is a promising technique for the transmitter to accurately acquire the CSI of massive multiple-input multiple-output (MIMO) systems.
NEPHELE: A Neural Platform for Highly Realistic Cloud Radiance Rendering
Using such a cloud platform compatible with neural rendering, we further showcase the capabilities of our cloud radiance rendering through a series of applications, ranging from cloud VR/AR rendering.
Incorporating Prior Knowledge of Latent Group Structure in Panel Data Models
We develop a constrained Bayesian grouped estimator that exploits researchers' prior beliefs on groups in a form of pairwise constraints, indicating whether a pair of units is likely to belong to a same group or different groups.
Easy Begun is Half Done: Spatial-Temporal Graph Modeling with ST-Curriculum Dropout
Spatial-temporal (ST) graph modeling, such as traffic speed forecasting and taxi demand prediction, is an important task in deep learning area.
Multi-task Deep Neural Networks for Massive MIMO CSI Feedback
Deep learning has been widely applied for the channel state information (CSI) feedback in frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) system.
When Will Arctic Sea Ice Disappear? Projections of Area, Extent, Thickness, and Volume
Rapidly diminishing Arctic summer sea ice is a strong signal of the pace of global climate change.
NeuVV: Neural Volumetric Videos with Immersive Rendering and Editing
We further develop a hybrid neural-rasterization rendering framework to support consumer-level VR headsets so that the aforementioned volumetric video viewing and editing, for the first time, can be conducted immersively in virtual 3D space.
On the Aggregation of Probability Assessments: Regularized Mixtures of Predictive Densities for Eurozone Inflation and Real Interest Rates
We propose methods for constructing regularized mixtures of density forecasts.
Forecasting with Bayesian Grouped Random Effects in Panel Data
In this paper, we estimate and leverage latent constant group structure to generate the point, set, and density forecasts for short dynamic panel data.
