activity
20172019
most citedAReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2019

On the Fairness of Disentangled Representations

Francesco Locatello, Gabriele Abbati, Tom Rainforth +3

Recently there has been a significant interest in learning disentangled representations, as they promise increased interpretability, generalization to unseen scenarios and faster l…

cs.LG20191 cited

AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs

Gabriele Abbati, Philippe Wenk, Michael A Osborne +3

Stochastic differential equations are an important modeling class in many disciplines. Consequently, there exist many methods relying on various discretization and numerical integr…

cs.LG2019

ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems

Philippe Wenk, Gabriele Abbati, Michael A Osborne +3

Parameter inference in ordinary differential equations is an important problem in many applied sciences and in engineering, especially in a data-scarce setting. In this work, we in…

stat.ML2018

MOrdReD: Memory-based Ordinal Regression Deep Neural Networks for Time Series Forecasting

Bernardo Pérez Orozco, Gabriele Abbati, Stephen Roberts

Time series forecasting is ubiquitous in the modern world. Applications range from health care to astronomy, and include climate modelling, financial trading and monitoring of crit…

stat.AP2017

MRI-based Surgical Planning for Lumbar Spinal Stenosis

Gabriele Abbati, Stefan Bauer, Peter J. Schüffler +5

The most common reason for spinal surgery in elderly patients is lumbar spinal stenosis(LSS). For LSS, treatment decisions based on clinical and radiological information as well as…