no code implementations • 25 Mar 2023 • Rickard Brüel-Gabrielsson, Tongzhou Wang, Manel Baradad, Justin Solomon
We use this observation to formulate a method for selecting which layer to target; in particular, our experimentation reveals that targeting deeper layers with Deep Augmentation outperforms augmenting the input data.
no code implementations • 2 Feb 2022 • Rickard Brüel-Gabrielsson, Chris Scarvelis
Meaning is defined by the company it keeps.
no code implementations • 29 Jan 2022 • Rickard Brüel-Gabrielsson, Mikhail Yurochkin, Justin Solomon
As a conservative alternative, we use positional encodings to expand receptive fields to $r$-hop neighborhoods.
1 code implementation • NeurIPS 2020 • Rickard Brüel-Gabrielsson
In this work we produce a framework for constructing universal function approximators on graph isomorphism classes.
3 code implementations • 29 May 2019 • Rickard Brüel-Gabrielsson, Bradley J. Nelson, Anjan Dwaraknath, Primoz Skraba, Leonidas J. Guibas, Gunnar Carlsson
Topology applied to real world data using persistent homology has started to find applications within machine learning, including deep learning.