Uncertainty-Aware Prognosis via Deep Gaussian Process von Biggio, Luca, Wieland, Alexander, Chao, Manuel Arias, Kastanis, Iason, Fink, Olga

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GEMTELLIGENCE: Accelerating gemstone classification with deep learning von Bendinelli, Tommaso, Biggio, Luca, Nyfeler, Daniel, Ghosh, Abhigyan, Tollan, Peter, Kirschmann, Moritz Alexander, Fink, Olga

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Fast emulation of two-point angular statistics for photometric galaxy surveys von Bonici, Marco, Biggio, Luca, Carbone, Carmelita, Guzzo, Luigi

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Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial von Nemani, Venkat, Biggio, Luca, Huan, Xun, Hu, Zhen, Fink, Olga, Tran, Anh, Wang, Yan, Zhang, Xiaoge, Hu, Chao

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Accelerating galaxy dynamical modeling using a neural network for joint lensing and kinematic analyses von Gomer, Matthew R., Ertl, Sebastian, Biggio, Luca, Wang, Han, Galan, Aymeric, Van de Vyvere, Lyne, Sluse, Dominique, Vernardos, Georgios, Suyu, Sherry H.

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Controllable Neural Symbolic Regression von Bendinelli, Tommaso, Biggio, Luca, Kamienny, Pierre-Alexandre

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Practical Evaluation of Poisoning Attacks on Online Anomaly Detectors in Industrial Control Systems von Kravchik, Moshe, Demetrio, Luca, Biggio, Battista, Shabtai, Asaf

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Harnessing Synthetic Datasets: The Role of Shape Bias in Deep Neural Network Generalization von Benarous, Elior, Anagnostidis, Sotiris, Biggio, Luca, Hofmann, Thomas

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Over-parameterization and Adversarial Robustness in Neural Networks: An Overview and Empirical Analysis von Chen, Zhang, Demetrio, Luca, Gupta, Srishti, Feng, Xiaoyi, Xia, Zhaoqiang, Cinà, Antonio Emanuele, Pintor, Maura, Oneto, Luca, Demontis, Ambra, Biggio, Battista, Roli, Fabio

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Gemtelligence: Accelerating Gemstone classification with Deep Learning von Bendinelli, Tommaso, Biggio, Luca, Nyfeler, Daniel, Ghosh, Abhigyan, Tollan, Peter, Kirschmann, Moritz Alexander, Fink, Olga

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An SDE for Modeling SAM: Theory and Insights von Compagnoni, Enea Monzio, Biggio, Luca, Orvieto, Antonio, Proske, Frank Norbert, Kersting, Hans, Lucchi, Aurelien

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Cosmology from Galaxy Redshift Surveys with PointNet von Anagnostidis, Sotiris, Thomsen, Arne, Kacprzak, Tomasz, Tröster, Tilman, Biggio, Luca, Refregier, Alexandre, Hofmann, Thomas

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Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A Tutorial von Nemani, Venkat, Biggio, Luca, Huan, Xun, Hu, Zhen, Fink, Olga, Tran, Anh, Wang, Yan, Zhang, Xiaoge, Hu, Chao

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Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers von Anagnostidis, Sotiris, Pavllo, Dario, Biggio, Luca, Noci, Lorenzo, Lucchi, Aurelien, Hofmann, Thomas

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Fast emulation of two-point angular statistics for photometric galaxy surveys von Bonici, Marco, Biggio, Luca, Carbone, Carmelita, Guzzo, Luigi

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Accelerating galaxy dynamical modeling using a neural network for joint lensing and kinematics analyses von Gomer, Matthew R, Ertl, Sebastian, Biggio, Luca, Wang, Han, Galan, Aymeric, Van de Vyvere, Lyne, Sluse, Dominique, Vernardos, Georgios, Suyu, Sherry H

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Dynaformer: A Deep Learning Model for Ageing-aware Battery Discharge Prediction von Biggio, Luca, Bendinelli, Tommaso, Kulkarni, Chetan, Fink, Olga

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Neural Symbolic Regression that Scales von Biggio, Luca, Bendinelli, Tommaso, Neitz, Alexander, Lucchi, Aurelien, Parascandolo, Giambattista

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Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse von Noci, Lorenzo, Anagnostidis, Sotiris, Biggio, Luca, Orvieto, Antonio, Singh, Sidak Pal, Lucchi, Aurelien

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On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics von Compagnoni, Enea Monzio, Scampicchio, Anna, Biggio, Luca, Orvieto, Antonio, Hofmann, Thomas, Teichmann, Josef

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