1 code implementation • 15 Apr 2024 • Krzysztof Kacprzyk, Mihaela van der Schaar
In this work, we investigate both of these challenges and propose a novel class of models, Shape Arithmetic Expressions (SHAREs), that fuses GAM's flexible shape functions with the complex feature interactions found in mathematical expressions.
2 code implementations • 16 Mar 2024 • Krzysztof Kacprzyk, Samuel Holt, Jeroen Berrevoets, Zhaozhi Qian, Mihaela van der Schaar
Above all, we consider the introduction of a completely new type of solution to be our most important contribution as it may spark entirely new innovations in treatment effects in general.
no code implementations • 3 Mar 2023 • Jeroen Berrevoets, Krzysztof Kacprzyk, Zhaozhi Qian, Mihaela van der Schaar
Our framework clearly identifies which assumptions are testable and which ones are not, such that the resulting solutions can be judiciously adopted in practice.
no code implementations • 1 Dec 2022 • Jeroen Berrevoets, Krzysztof Kacprzyk, Zhaozhi Qian, Mihaela van der Schaar
With CDL, researchers aim to structure and encode causal knowledge in the extremely flexible representation space of deep learning models.
no code implementations • ICLR 2022 • Zhaozhi Qian, Krzysztof Kacprzyk, Mihaela van der Schaar
In the experiments, D-CODE successfully discovered the governing equations of a diverse range of dynamical systems under challenging measurement settings with high noise and infrequent sampling.
no code implementations • 11 Mar 2021 • Peiyang He, Charlie Griffin, Krzysztof Kacprzyk, Artjom Joosen, Michael Collyer, Aleksandar Shtedritski, Yuki M. Asano
Privacy considerations and bias in datasets are quickly becoming high-priority issues that the computer vision community needs to face.