Sayna Ebrahimi

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berkeley college

Self-Supervised Pretraining Improves Self-Supervised Pretraining

While self-supervised pretraining has proven beneficial for many compute...
03/23/2021 ∙ by Colorado J. Reed, et al. ∙ 45 ∙ share

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Minimax Active Learning

Active learning aims to develop label-efficient algorithms by querying t...
12/18/2020 ∙ by Sayna Ebrahimi, et al. ∙ 0 ∙ share

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Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting

The goal of continual learning (CL) is to learn a sequence of tasks with...
10/04/2020 ∙ by Sayna Ebrahimi, et al. ∙ 9 ∙ share

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Adversarial Continual Learning

Continual learning aims to learn new tasks without forgetting previously...
03/21/2020 ∙ by Sayna Ebrahimi, et al. ∙ 8 ∙ share

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WiCV 2019: The Sixth Women In Computer Vision Workshop

In this paper we present the Women in Computer Vision Workshop - WiCV 20...
09/23/2019 ∙ by Irene Amerini, et al. ∙ 8 ∙ share

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Uncertainty-guided Continual Learning with Bayesian Neural Networks

Continual learning aims to learn new tasks without forgetting previously...
06/06/2019 ∙ by Sayna Ebrahimi, et al. ∙ 0 ∙ share

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Variational Adversarial Active Learning

Active learning aims to develop label-efficient algorithms by sampling t...
03/31/2019 ∙ by Samarth Sinha, et al. ∙ 0 ∙ share

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Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders

Many approaches in generalized zero-shot learning rely on cross-modal ma...
12/05/2018 ∙ by Edgar Schönfeld, et al. ∙ 0 ∙ share

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Compositional GAN: Learning Conditional Image Composition

Generative Adversarial Networks (GANs) can produce images of surprising ...
07/19/2018 ∙ by Samaneh Azadi, et al. ∙ 16 ∙ share

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Gradient-free Policy Architecture Search and Adaptation

We develop a method for policy architecture search and adaptation via gr...
10/16/2017 ∙ by Sayna Ebrahimi, et al. ∙ 0 ∙ share

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Sayna Ebrahimi

Featured Co-authors

Bo Li

Trevor Darrell

Kurt Keutzer

Joseph E. Gonzalez

Marcus Rohrbach

Zeynep Akata

Mohamed Elhoseiny

Roberto Calandra

Deepak Pathak

Anna Rohrbach

Arsha Nagrani

Self-Supervised Pretraining Improves Self-Supervised Pretraining

Minimax Active Learning

Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting

Adversarial Continual Learning

WiCV 2019: The Sixth Women In Computer Vision Workshop

Uncertainty-guided Continual Learning with Bayesian Neural Networks

Variational Adversarial Active Learning

Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders

Compositional GAN: Learning Conditional Image Composition

Gradient-free Policy Architecture Search and Adaptation