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Luca Daniel

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One step closer to unbiased aleatoric uncertainty estimation

Dec 20, 2023
Wang Zhang, Ziwen Ma, Subhro Das, Tsui-Wei Weng, Alexandre Megretski, Luca Daniel, Lam M. Nguyen

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Rare Event Probability Learning by Normalizing Flows

Oct 29, 2023
Zhenggqi Gao, Dinghuai Zhang, Luca Daniel, Duane S. Boning

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PIFON-EPT: MR-Based Electrical Property Tomography Using Physics-Informed Fourier Networks

Feb 24, 2023
Xinling Yu, José E. C. Serrallés, Ilias I. Giannakopoulos, Ziyue Liu, Luca Daniel, Riccardo Lattanzi, Zheng Zhang

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ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction

Feb 11, 2023
Wang Zhang, Tsui-Wei Weng, Subhro Das, Alexandre Megretski, Luca Daniel, Lam M. Nguyen

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Certified Interpretability Robustness for Class Activation Mapping

Jan 26, 2023
Alex Gu, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel

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MR-Based Electrical Property Reconstruction Using Physics-Informed Neural Networks

Oct 23, 2022
Xinling Yu, José E. C. Serrallés, Ilias I. Giannakopoulos, Ziyue Liu, Luca Daniel, Riccardo Lattanzi, Zheng Zhang

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SynBench: Task-Agnostic Benchmarking of Pretrained Representations using Synthetic Data

Oct 07, 2022
Ching-Yun Ko, Pin-Yu Chen, Jeet Mohapatra, Payel Das, Luca Daniel

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Learning from Multiple Annotator Noisy Labels via Sample-wise Label Fusion

Jul 22, 2022
Zhengqi Gao, Fan-Keng Sun, Mingran Yang, Sucheng Ren, Zikai Xiong, Marc Engeler, Antonio Burazer, Linda Wildling, Luca Daniel, Duane S. Boning

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Revisiting Contrastive Learning through the Lens of Neighborhood Component Analysis: an Integrated Framework

Dec 08, 2021
Ching-Yun Ko, Jeet Mohapatra, Sijia Liu, Pin-Yu Chen, Luca Daniel, Lily Weng

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Fast Training of Provably Robust Neural Networks by SingleProp

Feb 01, 2021
Akhilan Boopathy, Tsui-Wei Weng, Sijia Liu, Pin-Yu Chen, Gaoyuan Zhang, Luca Daniel

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