56 citations · 121 across the 14 of their papers we have counts for
5 papers · 1 filter
Datasets for Studying Generalization from Easy to Hard Examples
Avi Schwarzschild, Eitan Borgnia, Arjun Gupta +5
We describe new datasets for studying generalization from easy to hard examples.
Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks
Avi Schwarzschild, Eitan Borgnia, Arjun Gupta +4
Deep neural networks are powerful machines for visual pattern recognition, but reasoning tasks that are easy for humans may still be difficult for neural models. Humans possess the…
DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations
Eitan Borgnia, Jonas Geiping, Valeriia Cherepanova +6
Data poisoning and backdoor attacks manipulate training data to induce security breaches in a victim model. These attacks can be provably deflected using differentially private (DP…
The Uncanny Similarity of Recurrence and Depth
Avi Schwarzschild, Arjun Gupta, Amin Ghiasi +2
It is widely believed that deep neural networks contain layer specialization, wherein neural networks extract hierarchical features representing edges and patterns in shallow layer…
Kimera: from SLAM to Spatial Perception with 3D Dynamic Scene Graphs
Antoni Rosinol, Andrew Violette, Marcus Abate +5
Humans are able to form a complex mental model of the environment they move in. This mental model captures geometric and semantic aspects of the scene, describes the environment at…