Rickard Brüel Gabrielsson

According to our database, Rickard Brüel Gabrielsson authored at least 12 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Asymmetry in Low-Rank Adapters of Foundation Models.

Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon

CoRR, 2024

2023

Deep Augmentation: Enhancing Self-Supervised Learning through Transformations in Higher Activation Space.

Rickard Brüel Gabrielsson, Tongzhou Wang, Manel Baradad, Justin Solomon

CoRR, 2023

2022

Relative Position Prediction as Pre-training for Text Encoders.

Rickard Brüel Gabrielsson, Chris Scarvelis

CoRR, 2022

Rewiring with Positional Encodings for Graph Neural Networks.

Rickard Brüel Gabrielsson, Mikhail Yurochkin, Justin Solomon

CoRR, 2022

2020

Universal Function Approximation on Graphs using Multivalued Functions.

Rickard Brüel Gabrielsson

CoRR, 2020

Topology-Aware Surface Reconstruction for Point Clouds.

Rickard Brüel Gabrielsson, Vignesh Ganapathi-Subramanian, Primoz Skraba, Leonidas J. Guibas

Comput. Graph. Forum, 2020

Universal Function Approximation on Graphs.

Rickard Brüel Gabrielsson

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A Topology Layer for Machine Learning.

Rickard Brüel Gabrielsson, Bradley J. Nelson, Anjan Dwaraknath, Primoz Skraba

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

A Topology Layer for Machine Learning.

Rickard Brüel Gabrielsson, Bradley J. Nelson, Anjan Dwaraknath, Primoz Skraba, Leonidas J. Guibas, Gunnar E. Carlsson

CoRR, 2019

Exposition and Interpretation of the Topology of Neural Networks.

Rickard Brüel Gabrielsson, Gunnar E. Carlsson

Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

2018

Topological Approaches to Deep Learning.

Gunnar E. Carlsson, Rickard Brüel Gabrielsson

CoRR, 2018

A look at the topology of convolutional neural networks.

Rickard Brüel Gabrielsson, Gunnar E. Carlsson

CoRR, 2018