625 citations · 2.7k across the 69 of their papers we have counts for
7 papers · 1 filter
Ice Core Dating using Probabilistic Programming
Aditya Ravuri, Tom R. Andersson, Ieva Kazlauskaite +5
Ice cores record crucial information about past climate. However, before ice core data can have scientific value, the chronology must be inferred by estimating the age as a functio…
Modelling Technical and Biological Effects in scRNA-seq data with Scalable GPLVMs
Vidhi Lalchand, Aditya Ravuri, Emma Dann +6
Single-cell RNA-seq datasets are growing in size and complexity, enabling the study of cellular composition changes in various biological/clinical contexts. Scalable dimensionality…
Modeling the Machine Learning Multiverse
Samuel J. Bell, Onno P. Kampman, Jesse Dodge +1
Amid mounting concern about the reliability and credibility of machine learning research, we present a principled framework for making robust and generalizable claims: the multiver…
The Effect of Task Ordering in Continual Learning
Samuel J. Bell, Neil D. Lawrence
We investigate the effect of task ordering on continual learning performance. We conduct an extensive series of empirical experiments on synthetic and naturalistic datasets and sho…
An Empirical Evaluation of Flow Based Programming in the Machine Learning Deployment Context
Andrei Paleyes, Christian Cabrera, Neil D. Lawrence
As use of data driven technologies spreads, software engineers are more often faced with the task of solving a business problem using data-driven methods such as machine learning (…
Scalable Bigraphical Lasso: Two-way Sparse Network Inference for Count Data
Sijia Li, Martín López-García, Neil D. Lawrence +1
Classically, statistical datasets have a larger number of data points than features (). The standard model of classical statistics caters for the case where data points are…