activity
20182021
collaborators

5 papers

q-bio.QM2021

Uncertainty Estimation in SARS-CoV-2 B-cell Epitope Prediction for Vaccine Development

Bhargab Ghoshal, Biraja Ghoshal, Stephen Swift +1

B-cell epitopes play a key role in stimulating B-cells, triggering the primary immune response which results in antibody production as well as the establishment of long-term immuni…

eess.IV2020

Estimating Uncertainty and Interpretability in Deep Learning for Coronavirus (COVID-19) Detection

Biraja Ghoshal, Allan Tucker

Deep Learning has achieved state of the art performance in medical imaging. However, these methods for disease detection focus exclusively on improving the accuracy of classificati…

cs.LG2019

The Prevalence of Errors in Machine Learning Experiments

Martin Shepperd, Yuchen Guo, Ning Li +7

Context: Conducting experiments is central to research machine learning research to benchmark, evaluate and compare learning algorithms. Consequently it is important we conduct rel…

cs.DL2018

Specimens as research objects: reconciliation across distributed repositories to enable metadata propagation

Nicky Nicolson, Alan Paton, Sarah Phillips +1

Botanical specimens are shared as long-term consultable research objects in a global network of specimen repositories. Multiple specimens are generated from a shared field collecti…

stat.CO2018

Learning Bayesian Networks from Big Data with Greedy Search: Computational Complexity and Efficient Implementation

Marco Scutari, Claudia Vitolo, Allan Tucker

Learning the structure of Bayesian networks from data is known to be a computationally challenging, NP-hard problem. The literature has long investigated how to perform structure l…