no code implementations • 3 Mar 2024 • Sam Dauncey, Chris Holmes, Christopher Williams, Fabian Falck
In this work, we analyse using the gradient of a data point with respect to the parameters of the deep generative model for OOD detection, based on the simple intuition that OOD data should have larger gradient norms than training data.
Out-of-Distribution Detection Out of Distribution (OOD) Detection
1 code implementation • NeurIPS 2023 • Christopher Williams, Fabian Falck, George Deligiannidis, Chris Holmes, Arnaud Doucet, Saifuddin Syed
U-Nets are a go-to, state-of-the-art neural architecture across numerous tasks for continuous signals on a square such as images and Partial Differential Equations (PDE), however their design and architecture is understudied.
no code implementations • 19 Jan 2023 • Fabian Falck, Christopher Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris Holmes, Arnaud Doucet, Matthew Willetts
U-Net architectures are ubiquitous in state-of-the-art deep learning, however their regularisation properties and relationship to wavelets are understudied.
1 code implementation • 1 Mar 2022 • Oscar Clivio, Fabian Falck, Brieuc Lehmann, George Deligiannidis, Chris Holmes
We leverage these balancing scores to perform matching for high-dimensional causal inference and call this procedure neural score matching.
no code implementations • 30 Nov 2021 • Fabian Falck, Yuyin Zhou, Emma Rocheteau, Liyue Shen, Luis Oala, Girmaw Abebe, Subhrajit Roy, Stephen Pfohl, Emily Alsentzer, Matthew B. A. McDermott
A collection of the accepted abstracts for the Machine Learning for Health (ML4H) symposium 2021.
1 code implementation • NeurIPS 2021 • Fabian Falck, Haoting Zhang, Matthew Willetts, George Nicholson, Christopher Yau, Chris Holmes
Work in deep clustering focuses on finding a single partition of data.
1 code implementation • 4 Feb 2021 • Daniel Lenton, Fabio Pardo, Fabian Falck, Stephen James, Ronald Clark
We introduce Ivy, a templated Deep Learning (DL) framework which abstracts existing DL frameworks.
no code implementations • 19 Nov 2020 • Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Suproteem K. Sarkar, Subhrajit Roy, Stephanie L. Hyland
A collection of the accepted abstracts for the Machine Learning for Health (ML4H) workshop at NeurIPS 2020.
no code implementations • 24 Feb 2020 • Zoe Landgraf, Fabian Falck, Michael Bloesch, Stefan Leutenegger, Andrew Davison
Generally capable Spatial AI systems must build persistent scene representations where geometric models are combined with meaningful semantic labels.
no code implementations • 5 Feb 2020 • Matthew B. A. McDermott, Emily Alsentzer, Sam Finlayson, Michael Oberst, Fabian Falck, Tristan Naumann, Brett K. Beaulieu-Jones, Adrian V. Dalca
A collection of the accepted abstracts for the Machine Learning for Health (ML4H) workshop at NeurIPS 2019.
no code implementations • 12 Nov 2019 • Chufan Gao, Fabian Falck, Mononito Goswami, Anthony Wertz, Michael R. Pinsky, Artur Dubrawski
By analyzing the clusters of latent embeddings and visualizing them over time, we hypothesize that the clusters correspond to the physiological response patterns that match physicians' intuition.