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Equivariance Allows Handling Multiple Nuisance Variables When Analyzing
  Pooled Neuroimaging Datasets

Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets

29 March 2022
Vishnu Suresh Lokhande
Rudrasis Chakraborty
Sathya Ravi
Vikas Singh
ArXivPDFHTML

Papers citing "Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets"

3 / 3 papers shown
Title
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
M. Bronstein
Joan Bruna
Taco S. Cohen
Petar Velivcković
GNN
176
1,111
0
27 Apr 2021
Learning Invariant Representations using Inverse Contrastive Loss
Learning Invariant Representations using Inverse Contrastive Loss
A. K. Akash
Vishnu Suresh Lokhande
Sathya Ravi
Vikas Singh
SSL
21
8
0
16 Feb 2021
Patterns, predictions, and actions: A story about machine learning
Patterns, predictions, and actions: A story about machine learning
Moritz Hardt
Benjamin Recht
SSL
AI4TS
AI4CE
48
31
0
10 Feb 2021
1