Multi-Task Dynamical Systems

1 code implementation • 8 Oct 2022 • Alex Bird, Christopher K. I. Williams, Christopher Hawthorne

Time series datasets are often composed of a variety of sequences from the same domain, but from different entities, such as individuals, products, or organizations.

Multi-Task Learning Time Series +1

Pareto optimality, economy-effectiveness trade-offs and ion channel degeneracy: Improving population models of neurons

no code implementations • 12 Mar 2022 • Peter Jedlicka, Alex Bird, Hermann Cuntz

Furthermore, we hypothesize that Pareto optimality might contribute to our understanding of observed ion channel correlations in neurons.

Customizing Sequence Generation with Multi-Task Dynamical Systems

1 code implementation • 11 Oct 2019 • Alex Bird, Christopher K. I. Williams

Dynamical system models (including RNNs) often lack the ability to adapt the sequence generation or prediction to a given context, limiting their real-world application.

Style Transfer

Multi-Task Time Series Analysis applied to Drug Response Modelling

no code implementations • 21 Mar 2019 • Alex Bird, Christopher K. I. Williams, Christopher Hawthorne

Time series models such as dynamical systems are frequently fitted to a cohort of data, ignoring variation between individual entities such as patients.

Multi-Task Learning Time Series +1