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CryoETGAN: Cryo-Electron Tomography Image Synthesis via Unpaired Image Translation

Related publications (62)

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Weakly-Supervised Concept-based Adversarial Learning for Cross-lingual Word Embeddings

James Henderson

Distributed representations of words which map each word to a continuous vector have proven useful in capturing important linguistic information not only in a single language but also across different languages. Current unsupervised adversarial approaches ...

Association for Computational Linguistics2019

Bounding Inefficiency of Equilibria in Continuous Actions Games using Submodularity and Curvature

Maryam Kamgarpour, Andreas Krause

Games with continuous strategy sets arise in several machine learning problems (e.g. adversarial learning). For such games, simple no-regret learning algorithms exist in several cases and ensure convergence to coarse correlated equilibria (CCE). The effic ...

PMLR2019

Forged Authenticity: Governing Deepfake Risks

The manipulation of digital content is not a new phenomenon, but the application of machine learning to the creation of deepfakes has (i) radically improved the quality of output, (ii) slashed the resources required to produce realistic fakes at previously ...

EPFL International Risk Governance Center (IRGC)2019

Federated Learning with Bayesian Differential Privacy

Boi Faltings, Aleksei Triastcyn

We consider the problem of reinforcing federated learning with formal privacy guarantees. We propose to employ Bayesian differential privacy, a relaxation of differential privacy for similarly distributed data, to provide sharper privacy loss bounds. We ad ...

IEEE2019

Mean-Field methods for Structured Deep-Learning in Computer Vision

Pierre Bruno Baqué

In recent years, Machine Learning based Computer Vision techniques made impressive progress. These algorithms proved particularly efficient for image classification or detection of isolated objects. From a probabilistic perspective, these methods can predi ...

EPFL2018

Vision-based detection of aircrafts and UAVs

Artem Rozantsev

Unmanned Aerial Vehicles are becoming increasingly popular for a broad variety of tasks ranging from aerial imagery to objects delivery. With the expansion of the areas, where drones can be efficiently used, the collision risk with other flying objects inc ...

EPFL2017

Large-Scale Image Segmentation with Convolutional Networks

Pedro Henrique Oliveira Pinheiro

Object recognition is one of the most important problems in computer vision. However, visual recognition poses many challenges when tried to be reproduced by artificial systems. A main challenge is the problem of variability: objects can appear across huge ...

EPFL2017

Large-Scale Image Segmentation with Convolutional Networks

Pedro Henrique Oliveira Pinheiro

Sciences et Techniques de l’Ingénieur (STI)2017

DeepFool: a simple and accurate method to fool deep neural networks

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Alhussein Fawzi

State-of-the-art deep neural networks have achieved impressive results on many image classification tasks. However, these same architectures have been shown to be unstable to small, well sought, perturbations of the images. Despite the importance of this p ...

2016

From Image-level to Pixel-level Labeling with Convolutional Networks

Ronan Collobert, Pedro Henrique Oliveira Pinheiro

We are interested in inferring object segmentation by leveraging only object class information, and by considering only minimal priors on the object segmentation task. This problem could be viewed as a kind of weakly supervised segmentation task, and natur ...

2015