Tiziano Portenier

ETH Zurich — Switzerland

Computer Science · Physical Sciences

11h-index469citations37works11.02yr avg
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Research Topics

Generative Adversarial Networks and Image Synthesis(23), Domain Adaptation and Few-Shot Learning(10), Advanced Image Processing Techniques(9), Cell Image Analysis Techniques(7), Advanced Vision and Imaging(6)

Publications37 total

Generative feature-driven image replay for continual learning
Image and Vision Computing·2024· 11 cited
Learning Generative Models Using Denoising Density Estimators
IEEE Transactions on Neural Networks and Learning Systems·2023· 13 cited
Unpaired Translation from Semantic Label Maps to Images by Leveraging Domain-Specific Simulations
arXiv (Cornell University)·2023· 1 citedOpen Access
Probabilistic spatial analysis in quantitative microscopy with uncertainty-aware cell detection using deep Bayesian regression
Science Advances·2022· 7 citedOpen Access
Modality attention and sampling enables deep learning with heterogeneous marker combinations in fluorescence microscopy
Nature Machine Intelligence·2021· 17 citedOpen Access
Generative Feature-driven Image Replay for Continual Learning
arXiv (Cornell University)·2021· 3 citedOpen Access
Match What Matters: Generative Implicit Feature Replay for Continual Learning.
2021· 3 cited
Utilizing Uncertainty Estimation in Deep Learning Segmentation of Fluorescence Microscopy Images with Missing Markers
2021· 1 citedOpen Access
Learning ultrasound rendering from cross-sectional model slices for simulated training
International Journal of Computer Assisted Radiology and Surgery·2021· 7 citedOpen Access
Content-Preserving Unpaired Translation from Simulated to Realistic\n Ultrasound Images
arXiv (Cornell University)·2021· 1 citedOpen Access
Probabilistic Spatial Analysis in Quantitative Microscopy with Uncertainty-Aware Cell Detection using Deep Bayesian Regression of Density Maps
arXiv (Cornell University)·2021Open Access
Probabilistic Spatial Analysis in Quantitative Microscopy with\n Uncertainty-Aware Cell Detection using Deep Bayesian Regression of Density\n Maps
arXiv (Cornell University)·2021· 1 citedOpen Access
Utilizing Uncertainty Estimation in Deep Learning Segmentation of\n Fluorescence Microscopy Images with Missing Markers
arXiv (Cornell University)·2021Open Access
Learning to Take Directions One Step at a Time
2021· 4 cited
Content-Preserving Unpaired Translation from Simulated to Realistic Ultrasound Images
Lecture notes in computer science·2021· 1 citedOpen Access
Learning Ultrasound Rendering from Cross-Sectional Model Slices for Simulated Training
arXiv (Cornell University)·2021· 1 citedOpen Access
GramGAN: Deep 3D Texture Synthesis From 2D Exemplars
Repository for Publications and Research Data (ETH Zurich)·2021· 3 citedOpen Access
GramGAN: Deep 3D Texture Synthesis From 2D Exemplars
arXiv (Cornell University)·2020· 14 citedOpen Access
Learning Generative Models using Denoising Density Estimators
arXiv (Cornell University)·2020· 4 citedOpen Access
Deep Image Translation for Enhancing Simulated Ultrasound Images
Lecture notes in computer science·2020· 10 cited
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Frequent Co-authors

Matthias Zwicker(18), Orçun Göksel(18), Qiyang Hu(14), Paolo Favaro(14), Attila Szabó(8), Lin Zhang(7), Siavash Bigdeli(6), Álvaro Gomariz(6), César Nombela‐Arrieta(6), Kevin Thandiackal(3), Andrea Giovannini(3), Maria Gabrani(3), Shihao Wu(2), Hui Huang(2), Matan Sela(2), Ron Kimmel(2), Geng Lin(2), L. A. Dunbar(2), Christoph J. Paulus(2), Adrian Wälchli(2)