Damian Pascual

Distributed Computing Group
Computer Engineering and Networks Laboratory (TIK)
Department Electrical Engineering (D-ITET)
Office ETZ G 93
ETH Zurich
Gloriastrasse 35
8092 Zurich
Switzerland
phone | +41 44 63 27050 |
fax | +41 44 63 21036 |
Publications
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Telling BERT's Full Story: from Local Attention to Global Aggregation
Damian Pascual, Gino Brunner and Roger Wattenhofer.
The 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL), April 2021.
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WikiFlash: Generating Flashcards from Wikipedia Articles
Yuang Cheng, Yue Ding, Damian Pascual, Oliver Richter, Martin Volk and Roger Wattenhofer.
AAAI 2021 Workshop on AI Education - 35th AAAI Conference on Artificial Intelligence (AAAI), Online, February 2021.
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EpilepsyGAN: Synthetic Epileptic Brain Activities with Privacy Preservation
Damian Pascual, Alireza Amirshahi, Amir Aminifar, David Atienza, Philippe Ryvlin and Roger Wattenhofer.
IEEE Transactions on Biomedical Engineering, December 2020.
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Brain2Word: Improving Brain Decoding Methods and Evaluation (Oral presentation)
Nicolas Affolter, Béni Egressy, Damian Pascual and Roger Wattenhofer.
Medical Imaging Meets Neurips Workshop, Online, December 2020.
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Medley2K: A Dataset of Medley Transitions
Lukas Faber, Sandro Luck, Damian Pascual, Andreas Roth, Gino Brunner and Roger Wattenhofer.
13th International Workshop on Machine Learning and Music (MML at ECML-PKDD), Ghent, Belgium, September 2020.
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A Deep Learning Decoder for Long-Range Communication Systems
Damian Pascual, Simon Tanner, Mickey Vänskä and Roger Wattenhofer.
28th European Signal Processing Conference (EUSIPCO), Amsterdam, The Netherlands, August 2020.
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On Identifiability in Transformers
Gino Brunner, Yang Liu, Damian Pascual, Oliver Richter, Massimiliano Ciaramita and Roger Wattenhofer.
8th International Conference on Learning Representations (ICLR), Addis Ababa, Ethiopia, April 2020.
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Synthetic Epileptic Brain Activities using GANs
Damian Pascual, Amir Aminifar, David Atienza, Philippe Ryvlin and Roger Wattenhofer.
Machine Learning for Health (ML4H) at the 33rd Conference on Neural Information Processing Systems, Vancouver, Canada, December 2019.
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A Self-Learning Methodology for Epileptic Seizure Detection with Minimally Supervised Edge Labeling
Damian Pascual Ortiz, Amir Aminifar and David Atienza.
Design, Automation and Test in Europe (DATE), Florence, Italy, March 2019.
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