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machine learning; optimization; uncertainty quantification

Article: Jensen–Shannon divergence based novel loss functions for Bayesian neural networks

Submitted by susanta on
research
machine learning
Bayesian Neural Networks
Variational Inference
KL divergence
JS divergence
machine learning; optimization; uncertainty quantification

Ponkrshnan Thiagarajan, Susanta Ghosh, "Jensen–Shannon divergence based novel loss functions for Bayesian neural networks", Neurocomputing, 2024, 129115, ISSN 0925-2312.  https://doi.org/10.1016/j.neucom.2024.129115  

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[Abstracts due Feb 5] Our usual ML, UQ and Optimization mini-symposium @ USNCCM2021

Submitted by mbessa on
conference
machine learning; optimization; uncertainty quantification

Dear colleagues,

Deadline to submit your abstract to USNCCM2021 is fast approacing (Februart 5). If you are working with machine learning, uncertainty quantification, optimization or a related topic, consider the following symposia:

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