4 code implementations • 2 Feb 2020 • Roxana Pamfil, Nisara Sriwattanaworachai, Shaan Desai, Philip Pilgerstorfer, Paul Beaumont, Konstantinos Georgatzis, Bryon Aragam
Compared to state-of-the-art methods for learning dynamic Bayesian networks, our method is both scalable and accurate on real data.
no code implementations • 18 Dec 2019 • Marc-Andre Schulz, Matt Chapman-Rounds, Manisha Verma, Danilo Bzdok, Konstantinos Georgatzis
The distribution of instances in the explanation space of our diagnostic classifier amplifies the different reasons for belonging to the same class - resulting in a representation that is uniquely useful for discovering latent subtypes.
no code implementations • 2 Dec 2019 • Matt Chapman-Rounds, Marc-Andre Schulz, Erik Pazos, Konstantinos Georgatzis
Modern instance-based model-agnostic explanation methods (LIME, SHAP, L2X) are of great use in data-heavy industries for model diagnostics, and for end-user explanations.
no code implementations • 4 Nov 2019 • Giulio Morina, Viktoriia Oliinyk, Julian Waton, Ines Marusic, Konstantinos Georgatzis
Machine learning algorithms are extensively used to make increasingly more consequential decisions about people, so achieving optimal predictive performance can no longer be the only focus.
no code implementations • 31 Jul 2016 • Konstantinos Georgatzis, Christopher K. I. Williams, Christopher Hawthorne
We present a non-linear dynamical system for modelling the effect of drug infusions on the vital signs of patients admitted in Intensive Care Units (ICUs).
no code implementations • 24 Apr 2015 • Konstantinos Georgatzis, Christopher K. I. Williams
We present a Discriminative Switching Linear Dynamical System (DSLDS) applied to patient monitoring in Intensive Care Units (ICUs).