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07/13/2023
Multi-view self-supervised learning for multivariate variable-channel time series
Labeling of multivariate biomedical time series data is a laborious and ...
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06/23/2023
Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity
In federated learning, data heterogeneity is a critical challenge. A str...
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12/05/2022
Partial Variance Reduction improves Non-Convex Federated learning on heterogeneous data
Data heterogeneity across clients is a key challenge in federated learni...
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11/26/2022
End-to-End Learning for VCSEL-based Optical Interconnects: State-of-the-Art, Challenges, and Opportunities
Optical interconnects (OIs) based on vertical-cavity surface-emitting la...
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02/25/2022
Raman Spectrum Matching with Contrastive Representation Learning
Raman spectroscopy is an effective, low-cost, non-intrusive technique of...
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07/13/2021
Calibrated Uncertainty for Molecular Property Prediction using Ensembles of Message Passing Neural Networks
Data-driven methods based on machine learning have the potential to acce...
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06/21/2018
Probabilistic PARAFAC2
The PARAFAC2 is a multimodal factor analysis model suitable for analyzin...
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06/08/2018
Neural Message Passing with Edge Updates for Predicting Properties of Molecules and Materials
Neural message passing on molecular graphs is one of the most promising ...
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01/04/2016
Nonparametric Modeling of Dynamic Functional Connectivity in fMRI Data
Dynamic functional connectivity (FC) has in recent years become a topic ...
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08/12/2015
Bayesian Dropout
Dropout has recently emerged as a powerful and simple method for trainin...
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05/31/2014
Adaptive Reconfiguration Moves for Dirichlet Mixtures
Bayesian mixture models are widely applied for unsupervised learning and...
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12/20/2013
Non-parametric Bayesian modeling of complex networks
Modeling structure in complex networks using Bayesian non-parametrics ma...
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11/11/2013
