Zeynep Akata

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Max Planck Society ∙ University of Amsterdam

Senior Researcher at Max-Planck-Institut für Informatik

Learning Robust Representations via Multi-View Information Bottleneck

The information bottleneck principle provides an information-theoretic m...
02/17/2020 ∙ by Marco Federici, et al. ∙ 34 ∙ share

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Understanding Misclassifications by Attributes

In this paper, we aim to understand and explain the decisions of deep ne...
10/15/2019 ∙ by Sadaf Gulshad, et al. ∙ 27 ∙ share

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e-SNLI-VE-2.0: Corrected Visual-Textual Entailment with Natural Language Explanations

The recently proposed SNLI-VE corpus for recognising visual-textual enta...
04/07/2020 ∙ by Virginie Do, et al. ∙ 13 ∙ share

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Visual Rationalizations in Deep Reinforcement Learning for Atari Games

Due to the capability of deep learning to perform well in high dimension...
02/01/2019 ∙ by Laurens Weitkamp, et al. ∙ 10 ∙ share

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Combining Generative and Discriminative Models for Hybrid Inference

A graphical model is a structured representation of the data generating ...
06/06/2019 ∙ by Victor Garcia Satorras, et al. ∙ 8 ∙ share

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Evaluating Weakly Supervised Object Localization Methods Right

Weakly-supervised object localization (WSOL) has gained popularity over ...
01/21/2020 ∙ by Junsuk Choe, et al. ∙ 7 ∙ share

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Relational Generalized Few-Shot Learning

Transferring learned models to novel tasks is a challenging problem, par...
07/22/2019 ∙ by Xiahan Shi, et al. ∙ 3 ∙ share

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Primal-Dual Wasserstein GAN

We introduce Primal-Dual Wasserstein GAN, a new learning algorithm for b...
05/24/2018 ∙ by Mevlana Gemici, et al. ∙ 2 ∙ share

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Textual Explanations for Self-Driving Vehicles

Deep neural perception and control networks have become key components o...
07/30/2018 ∙ by Jinkyu Kim, et al. ∙ 2 ∙ share

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Manipulating Attributes of Natural Scenes via Hallucination

In this study, we explore building a two-stage framework for enabling us...
08/22/2018 ∙ by Levent Karacan, et al. ∙ 2 ∙ share

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Multimodal Explanations: Justifying Decisions and Pointing to the Evidence

Deep models that are both effective and explainable are desirable in man...
02/15/2018 ∙ by Dong Huk Park, et al. ∙ 1 ∙ share

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Generating Counterfactual Explanations with Natural Language

Natural language explanations of deep neural network decisions provide a...
06/26/2018 ∙ by Lisa Anne Hendricks, et al. ∙ 1 ∙ share

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Feature Generating Networks for Zero-Shot Learning

Suffering from the extreme training data imbalance between seen and unse...
12/04/2017 ∙ by Yongqin Xian, et al. ∙ 0 ∙ share

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Attentive Explanations: Justifying Decisions and Pointing to the Evidence (Extended Abstract)

Deep models are the defacto standard in visual decision problems due to ...
11/17/2017 ∙ by Dong Huk Park, et al. ∙ 0 ∙ share

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Grounding Visual Explanations (Extended Abstract)

Existing models which generate textual explanations enforce task relevan...
11/17/2017 ∙ by Lisa Anne Hendricks, et al. ∙ 0 ∙ share

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Generative Adversarial Text to Image Synthesis

Automatic synthesis of realistic images from text would be interesting a...
05/17/2016 ∙ by Scott Reed, et al. ∙ 0 ∙ share

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Zero-Shot Learning - A Comprehensive Evaluation of the Good, the Bad and the Ugly

Due to the importance of zero-shot learning, i.e. classifying images whe...
07/03/2017 ∙ by Yongqin Xian, et al. ∙ 0 ∙ share

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Channel-Recurrent Variational Autoencoders

Variational Autoencoder (VAE) is an efficient framework in modeling natu...
06/12/2017 ∙ by Wenling Shang, et al. ∙ 0 ∙ share

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Zero-Shot Learning - The Good, the Bad and the Ugly

Due to the importance of zero-shot learning, the number of proposed appr...
03/13/2017 ∙ by Yongqin Xian, et al. ∙ 0 ∙ share

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Exploiting saliency for object segmentation from image level labels

There have been remarkable improvements in the semantic labelling task i...
01/28/2017 ∙ by Seong Joon Oh, et al. ∙ 0 ∙ share

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Learning to Generate Images of Outdoor Scenes from Attributes and Semantic Layouts

Automatic image synthesis research has been rapidly growing with deep ne...
12/01/2016 ∙ by Levent Karacan, et al. ∙ 0 ∙ share

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Gaze Embeddings for Zero-Shot Image Classification

Zero-shot image classification using auxiliary information, such as attr...
11/28/2016 ∙ by Nour Karessli, et al. ∙ 0 ∙ share

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Learning What and Where to Draw

Generative Adversarial Networks (GANs) have recently demonstrated the ca...
10/08/2016 ∙ by Scott Reed, et al. ∙ 0 ∙ share

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Latent Embeddings for Zero-shot Classification

We present a novel latent embedding model for learning a compatibility f...
03/29/2016 ∙ by Yongqin Xian, et al. ∙ 0 ∙ share

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Multi-Cue Zero-Shot Learning with Strong Supervision

Scaling up visual category recognition to large numbers of classes remai...
03/29/2016 ∙ by Zeynep Akata, et al. ∙ 0 ∙ share

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Label-Embedding for Image Classification

Attributes act as intermediate representations that enable parameter sha...
03/30/2015 ∙ by Zeynep Akata, et al. ∙ 0 ∙ share

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Evaluation of Output Embeddings for Fine-Grained Image Classification

Image classification has advanced significantly in recent years with the...
09/30/2014 ∙ by Zeynep Akata, et al. ∙ 0 ∙ share

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Attentive Explanations: Justifying Decisions and Pointing to the Evidence

Deep models are the defacto standard in visual decision models due to th...
12/14/2016 ∙ by Dong Huk Park, et al. ∙ 0 ∙ share

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Generating Visual Explanations

Clearly explaining a rationale for a classification decision to an end-u...
03/28/2016 ∙ by Lisa Anne Hendricks, et al. ∙ 0 ∙ share

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Grounding Visual Explanations

Existing visual explanation generating agents learn to fluently justify ...
07/25/2018 ∙ by Lisa Anne Hendricks, 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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XOC: Explainable Observer-Classifier for Explainable Binary Decisions

When deep neural networks optimize highly complex functions, it is not a...
02/05/2019 ∙ by Stephan Alaniz, et al. ∙ 0 ∙ share

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Semantically Tied Paired Cycle Consistency for Zero-Shot Sketch-based Image Retrieval

Zero-shot sketch-based image retrieval (SBIR) is an emerging task in com...
03/08/2019 ∙ by Anjan Dutta, et al. ∙ 0 ∙ share

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f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning

When labeled training data is scarce, a promising data augmentation appr...
03/25/2019 ∙ by Yongqin Xian, et al. ∙ 0 ∙ share

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Interpreting Adversarial Examples with Attributes

Deep computer vision systems being vulnerable to imperceptible and caref...
04/17/2019 ∙ by Sadaf Gulshad, et al. ∙ 0 ∙ share

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Bayesian Zero-Shot Learning

Object classes that surround us have a natural tendency to emerge at var...
07/22/2019 ∙ by Sarkhan Badirli, et al. ∙ 0 ∙ share

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Modeling Conceptual Understanding in Image Reference Games

An agent who interacts with a wide population of other agents needs to b...
10/10/2019 ∙ by Rodolfo Corona, et al. ∙ 0 ∙ share

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Zeynep Akata

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