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09/13/2023
Limited-Angle Tomography Reconstruction via Deep End-To-End Learning on Synthetic Data
Computed tomography (CT) has become an essential part of modern science ...
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08/22/2023
A Survey on Self-Supervised Representation Learning
Learning meaningful representations is at the heart of many tasks in the...
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03/13/2023
Transformer-based World Models Are Happy With 100k Interactions
Deep neural networks have been successful in many reinforcement learning...
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05/31/2022
Optimizing Intermediate Representations of Generative Models for Phase Retrieval
Phase retrieval is the problem of reconstructing images from magnitude-o...
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05/30/2022
Deblurring Photographs of Characters Using Deep Neural Networks
In this paper, we present our approach for the Helsinki Deblur Challenge...
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10/26/2021
A Closer Look at Reference Learning for Fourier Phase Retrieval
Reconstructing images from their Fourier magnitude measurements is a pro...
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07/09/2021
Learning to Detect Adversarial Examples Based on Class Scores
Given the increasing threat of adversarial attacks on deep neural networ...
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06/18/2021
Non-Iterative Phase Retrieval With Cascaded Neural Networks
Fourier phase retrieval is the problem of reconstructing a signal given ...
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06/18/2021
Learning to Plan via a Multi-Step Policy Regression Method
We propose a new approach to increase inference performance in environme...
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10/12/2020
Discrete Latent Space World Models for Reinforcement Learning
Sample efficiency remains a fundamental issue of reinforcement learning....
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06/26/2020
Fast Multi-Level Foreground Estimation
Alpha matting aims to estimate the translucency of an object in a given ...
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03/25/2020
PyMatting: A Python Library for Alpha Matting
An important step of many image editing tasks is to extract specific obj...
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12/10/2019
Phase Retrieval using Conditional Generative Adversarial Networks
In this paper, we propose the application of conditional generative adve...
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06/09/2019
