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20212023
most citedSource-Free Adaptation to Measurement Shift via Bottom-Up Feature Restoration

3 citations · 4 across the 4 of their papers we have counts for

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cs.LG2023★ 1 cited

Modularity Trumps Invariance for Compositional Robustness

Ian Mason, Anirban Sarkar, Tomotake Sasaki +1

By default neural networks are not robust to changes in data distribution. This has been demonstrated with simple image corruptions, such as blurring or adding noise, degrading ima…

cs.LG2023

Deephys: Deep Electrophysiology, Debugging Neural Networks under Distribution Shifts

Anirban Sarkar, Matthew Groth, Ian Mason +2

Deep Neural Networks (DNNs) often fail in out-of-distribution scenarios. In this paper, we introduce a tool to visualize and understand such failures. We draw inspiration from conc…