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05/22/2023
Representing Input Transformations by Low-Dimensional Parameter Subspaces
Deep models lack robustness to simple input transformations such as rota...
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04/27/2023
DataComp: In search of the next generation of multimodal datasets
Large multimodal datasets have been instrumental in recent breakthroughs...
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02/27/2023
The Role of Pre-training Data in Transfer Learning
The transfer learning paradigm of model pre-training and subsequent fine...
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11/15/2022
REPAIR: REnormalizing Permuted Activations for Interpolation Repair
In this paper we look into the conjecture of Entezari et al.(2021) which...
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07/01/2022
Studying the impact of magnitude pruning on contrastive learning methods
We study the impact of different pruning techniques on the representatio...
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06/22/2022
Understanding the effect of sparsity on neural networks robustness
This paper examines the impact of static sparsity on the robustness of a...
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06/15/2022
Deep Neural Network Pruning for Nuclei Instance Segmentation in Hematoxylin Eosin-Stained Histological Images
Recently, pruning deep neural networks (DNNs) has received a lot of atte...
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10/12/2021
The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks
In this paper, we conjecture that if the permutation invariance of neura...
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11/19/2020
Interpretable and Transferable Models to Understand the Impact of Lockdown Measures on Local Air Quality
The COVID-19 related lockdown measures offer a unique opportunity to und...
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09/23/2019