Learning new physics from an imperfect machine

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The prediction of algal blooms using traditional water quality indicators is expensive, labor-intensive, and timeconsuming, making it challenging to meet the critical requirement of timely monitoring for prompt management. Using optical measures for foreca ...

This work proposes a method to measure the photon polarisation in

B^+ \rightarrow K^+ \pi^- \pi^+ \gamma

decays and prepares the necessary elements for this measurement using the data sets collected by the LHCb experiment at CERN in

2011

2012

, $2016 ...

Learning new physics from an imperfect machine

Chat with Graph Search

Learnable latent embeddings for joint behavioural and neural analysis

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Partial Information Sharing Over Social Learning Networks

Time vs. Truth: Age-Distortion Tradeoffs and Strategies for Distributed Inference

Bayes-optimal Learning of Deep Random Networks of Extensive-width

On double-descent in uncertainty quantification in overparametrized models

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

Layer-Wise Learning Framework for Efficient DNN Deployment in Biomedical Wearable Systems

Breaking the Curse of Dimensionality in Deep Neural Networks by Learning Invariant Representations

Expectation consistency for calibration of neural networks

Improving algal bloom detection using spectroscopic analysis and machine learning: A case study in a large artificial reservoir, South Korea

Amplitude analysis for the measurement of the photon polarisation in B rightarrow K pi pi gamma decays