Search Results - "Lucchi, Aurélien"

Quantum Generative Adversarial Networks for learning and loading random distributions by Zoufal, Christa, Lucchi, Aurélien, Woerner, Stefan

“…Quantum algorithms have the potential to outperform their classical counterparts in a variety of tasks. The realization of the advantage often requires the…”
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Variational quantum Boltzmann machines by Zoufal, Christa, Lucchi, Aurélien, Woerner, Stefan

“…This work presents a novel realization approach to quantum Boltzmann machines (QBMs). The preparation of the required Gibbs states, as well as the evaluation…”
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A convolutional neural network for classifying cloud particles recorded by imaging probes by Touloupas, Georgios, Lauber, Annika, Henneberger, Jan, Beck, Alexander, Lucchi, Aurélien

“…During typical field campaigns, millions of cloud particle images are captured with imaging probes. Our interest lies in classifying these particles in order…”
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Learning Aerial Image Segmentation From Online Maps by Kaiser, Pascal, Wegner, Jan Dirk, Lucchi, Aurelien, Jaggi, Martin, Hofmann, Thomas, Schindler, Konrad

“…This paper deals with semantic segmentation of high-resolution (aerial) images where a semantic class label is assigned to each pixel via supervised…”
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A fully automated approach to segmentation of irregularly shaped cellular structures in EM images by Lucchi, Aurélien, Smith, Kevin, Achanta, Radhakrishna, Lepetit, Vincent, Fua, Pascal

“…While there has been substantial progress in segmenting natural images, state-of-the-art methods that perform well in such tasks unfortunately tend to…”
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Are spatial and global constraints really necessary for segmentation? by Lucchi, A., Yunpeng Li, Boix, X., Smith, K., Fua, P.

“…Many state-of-the-art segmentation algorithms rely on Markov or Conditional Random Field models designed to enforce spatial and global consistency constraints…”
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Supervoxel-Based Segmentation of Mitochondria in EM Image Stacks With Learned Shape Features by Lucchi, A., Smith, K., Achanta, R., Knott, G., Fua, P.

“…It is becoming increasingly clear that mitochondria play an important role in neural function. Recent studies show mitochondrial morphology to be crucial to…”
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Exploiting enclosing membranes and contextual cues for mitochondria segmentation by Lucchi, Aurélien, Becker, Carlos, Neila, Pablo Márquez, Fua, Pascal

“…In this paper, we improve upon earlier approaches to segmenting mitochondria in Electron Microscopy images by explicitly modeling the double membrane that…”
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Emulation of Cosmological Mass Maps with Conditional Generative Adversarial Networks by Perraudin, Nathanaël, Marcon, Sandro, Lucchi, Aurelien, Kacprzak, Tomasz

“…Weak gravitational lensing mass maps play a crucial role in understanding the evolution of structures in the Universe and our ability to constrain cosmological…”
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A sub-sampled tensor method for nonconvex optimization by Lucchi, Aurelien, Kohler, Jonas

“…Abstract A significant theoretical advantage of high-order optimization methods is their superior convergence guarantees. For instance, third-order regularized…”
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Topological Map Extraction From Overhead Images by Li, Zuoyue, Wegner, Jan Dirk, Lucchi, Aurelien

“…We propose a new approach, named PolyMapper, to circumvent the conventional pixel-wise segmentation of (aerial) images and predict objects in a vector…”
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The power of quantum neural networks by Abbas, Amira, Sutter, David, Zoufal, Christa, Lucchi, Aurelien, Figalli, Alessio, Woerner, Stefan

“…It is unknown whether near-term quantum computers are advantageous for machine learning tasks. In this work we address this question by trying to understand…”
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A machine learning-based surrogate model to approximate optimal building retrofit solutions by Thrampoulidis, Emmanouil, Mavromatidis, Georgios, Lucchi, Aurelien, Orehounig, Kristina

“…•Machine learning-based surrogate model to predict near-optimal retrofit solutions.•Validated with a conventional building simulation-optimization model.•Case…”
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SLIC Superpixels Compared to State-of-the-Art Superpixel Methods by Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., Süsstrunk, Sabine

“…Computer vision applications have come to rely increasingly on superpixels in recent years, but it is not always clear what constitutes a good superpixel…”
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Learning Generative Models of Textured 3D Meshes from Real-World Images by Pavllo, Dario, Kohler, Jonas, Hofmann, Thomas, Lucchi, Aurelien

“…Recent advances in differentiable rendering have sparked an interest in learning generative models of textured 3D meshes from image collections. These models…”
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Generalization Through The Lens Of Leave-One-Out Error by Bachmann, Gregor, Hofmann, Thomas, Lucchi, Aurélien

“…Despite the tremendous empirical success of deep learning models to solve various learning tasks, our theoretical understanding of their generalization ability…”
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Variational Quantum Boltzmann Machines by Zoufal, Christa, Lucchi, Aurélien, Woerner, Stefan

“…Quantum Machine Intelligence vol. 3, Article number: 7 (2021) This work presents a novel realization approach to Quantum Boltzmann Machines (QBMs). The…”
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Learning for Structured Prediction Using Approximate Subgradient Descent with Working Sets by Lucchi, Aurelien, Yunpeng Li, Fua, Pascal

“…We propose a working set based approximate sub gradient descent algorithm to minimize the margin-sensitive hinge loss arising from the soft constraints in…”
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Learning Structured Models for Segmentation of 2-D and 3-D Imagery by Lucchi, Aurelien, Marquez-Neila, Pablo, Becker, Carlos, Li, Yunpeng, Smith, Kevin, Knott, Graham, Fua, Pascal

“…Efficient and accurate segmentation of cellular structures in microscopic data is an essential task in medical imaging. Many state-of-the-art approaches to…”
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Quantum Generative Adversarial Networks for Learning and Loading Random Distributions by Zoufal, Christa, Lucchi, Aurélien, Woerner, Stefan

“…npj Quantum Inf 5, 103 (2019) Quantum algorithms have the potential to outperform their classical counterparts in a variety of tasks. The realization of the…”
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