Sayna Ebrahimi

is this you? claim profile

0 followers
berkeley college

Minimax Active Learning

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

read it
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

read it
Adversarial Continual Learning

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

read it
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

read it
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

read it
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

read it
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

read it
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

read it
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

read it

Sayna Ebrahimi

Featured Co-authors

Trevor Darrell

Joseph E. Gonzalez

Marcus Rohrbach

Zeynep Akata

Mohamed Elhoseiny

Roberto Calandra

Deepak Pathak

Anna Rohrbach

Franziska Meier

Arsha Nagrani

Amaia Salvador

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