4M: Massively Multimodal Masked Modeling

no code implementations • NeurIPS 2023 • David Mizrahi, Roman Bachmann, Oğuzhan Fatih Kar, Teresa Yeo, Mingfei Gao, Afshin Dehghan, Amir Zamir

Current machine learning models for vision are often highly specialized and limited to a single modality and task.

MultiMAE: Multi-modal Multi-task Masked Autoencoders

1 code implementation • 4 Apr 2022 • Roman Bachmann, David Mizrahi, Andrei Atanov, Amir Zamir

We show this pre-training strategy leads to a flexible, simple, and efficient framework with improved transfer results to downstream tasks.

Depth Estimation Image Classification +1

[Re] Can gradient clipping mitigate label noise?

1 code implementation • RC 2020 • David Mizrahi, Oğuz Kaan Yüksel, Aiday Marlen Kyzy

Nonetheless, with the help of an additional experiment, our results support the authorsʼ claim that partially Huberised losses perform well on real-world datasets subject to label noise.

Learning with noisy labels