Sohan Seth

Latest

• Computational Fluorescence Suppression in Shifted Excitation Raman Spectroscopy
• Grouped representation of interatomic distances as a similarity measure for crystal structures
• Simultaneous Spectral Temporal Modelling for a Time-Resolved Fluorescence Emission Spectrum
• Census-independent population estimation using representation learning
• Distinct clinical symptom patterns in patients hospitalised with COVID-19 in an analysis of 59,011 patients in the ISARIC-4C study
• Using open-source data to construct 20 metre resolution maps of children’s travel time to the nearest health facility
• Studying the Long-term Impact of COVID-19 in Kids (SLICK). Healthcare use and costs in children and young people following community-acquired SARS-CoV-2 infection: protocol for an observational study using linked primary and secondary routinely collected healthcare data from England, Scotland and Wales
• Studying the Long-term Impact of COVID-19 in Kids (SLICK). Healthcare use and costs in children and young people following community-acquired SARS-CoV-2 infection: protocol for an observational study using linked primary and secondary routinely collected healthcare data from England, Scotland and Wales
• Tri‐mode optical biopsy probe with fluorescence endomicroscopy, Raman spectroscopy, and time‐resolved fluorescence spectroscopy
• Grouped representation of interatomic distances as a similarity measure for crystal structures
• Influence of pore fluid pressure and differential stress on gypsum dehydration and rock texture revealed by 4D synchrotron X-ray tomography
• Prediction of the performance of pre‐packed purification columns through machine learning
• Census-Independent Population Estimation using Representation Learning
• Fast Segmentation of 4D Microtomography Volumes from Core-flooding Experiments in Porous Rock using Convolutional Neural Network
• Towards Sustainable Census-Independent Population Estimation in Mozambique
• Child Poverty and Access to Services in Uganda
• Clinical characteristics of children and young people admitted to hospital with covid-19 in United Kingdom: prospective multicentre observational cohort study
• Robust, reproducible clinical patterns in hospitalised patients with COVID-19
• Interpretable Descriptors for Materials Machine Learning
• scID Uses Discriminant Analysis to Identify Transcriptionally Equivalent Cell Types across Single-Cell RNA-Seq Data with Batch Effect
• Model Criticism in Latent Space
• Endoscopic sensing of distal lung physiology
• Stratification of Fibrotic Lung Disease: Integration of Molecular Endotyping and Quantitative CT via Machine Learning
• Estimating Bacterial and Cellular Load in FCFM Imaging
• Endoscopic sensing of pH in the distal lung (Conference Presentation)
• Estimating Bacterial Load in FCFM Imaging
• Assessing the utility of autofluorescence-based pulmonary optical endomicroscopy to predict the malignant potential of solitary pulmonary nodules in humans
• Archetypal Analysis for Nominal Observations
• Modelling-based experiment retrieval: a case study with gene expression clustering
• Probabilistic archetypal analysis
• Quantized mixture kernel least mean square
• Exploration and retrieval of whole-metagenome sequencing samples
• Probabilistic kernel least mean squares algorithms
• Differential analysis of whole-genome shotgun sequences
• Learning dependence from samples
• Retrieval of Experiments by Efficient Comparison of Marginal Likelihoods
• Mixture kernel least mean square
• Adaptive Inverse Control of Neural Spatiotemporal Spike Patterns With a Reproducing Kernel Hilbert Space (RKHS) Framework
• Kernel Methods on Spike Train Space for Neuroscience: A Tutorial
• Strictly Positive-Definite Spike Train Kernels for Point-Process Divergences
• Conditional Association
• Online efficient learning with quantized KLMS and L1 regularization
• Analyzing dependence structure of the human brain in response to visual stimuli
• Functional Connectivity Dynamics Among Cortical Neurons: A Dependence Analysis
• An adaptive decoder from spike trains to micro-stimulation using kernel least-mean-squares (KLMS)
• A Unified Framework for Quadratic Measures of Independence
• Evaluating dependence in spike train metric spaces
• A metric approach toward point process divergence
• Estimation of symmetric chi-square divergence for point processes
• A test of independence based on a generalized correlation function
• Variable Selection: A Statistical Dependence Perspective
• A conditional independence perspective of variable selection
• A Test of Granger Non-causality Based on Nonparametric Conditional Independence
• A conditional distribution function based approach to design nonparametric tests of independence and conditional independence
• Correntropy for Random Variables: Properties and Applications in Statistical Inference
• Estimation of density ratio and its application to design a measure of dependence
• On speeding up computation in information theoretic learning
• A new nonparametric measure of conditional independence
• Compressed signal reconstruction using the correntropy induced metric
• Signal Processing with Echo State Networks in the Complex Domain
• Monitoring of black tea fermentation process using electronic nose
• Detection of optimum fermentation time for black tea manufacturing using electronic nose
• Census-Independent Population Density Estimation in Mozambique
• Data-driven Insight and Prediction in Later Life Care
• Machine Learning for Spectroscopy
• Segmentation of Micro-tomography Images for Understanding Deformation of Rocks