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Itay Benou

3 accepted papers

2025

Show and Tell: Visually Explainable Deep Neural Nets via Spatially-Aware Concept Bottleneck Models

CVPR 2025highlight

Modern deep neural networks have now reached human-level performance across a variety of tasks. However, unlike humans they lack the ability to explain their decisions by showing where and telling what concepts guided them. In this work, we present a unified framework for transforming any vision neu…

Cited by 0SourcePDFScholar
2025

TractoTransformer: Diffusion MRI Streamline Tractography using CNN and Transformer Networks

NeurIPS 2025poster

White matter tractography is an advanced neuroimaging technique that reconstructs the 3D white matter pathways of the brain from diffusion MRI data. It can be framed as a pathfinding problem aiming to infer neural fiber trajectories from noisy and ambiguous measurements, facing challenges such as cr…

Cited by 0SourceScholar
2022

Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images

ICML 2022spotlight

Despite remarkable progress on visual recognition tasks, deep neural-nets still struggle to generalize well when training data is scarce or highly imbalanced, rendering them extremely vulnerable to real-world examples. In this paper, we present a surprisingly simple yet highly effective method to mi…