2.3k citations · 3.8k across the 24 of their papers we have counts for
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Distance-Based Learning from Errors for Confidence Calibration
Chen Xing, Sercan Arik, Zizhao Zhang +1
Deep neural networks (DNNs) are poorly calibrated when trained in conventional ways. To improve confidence calibration of DNNs, we propose a novel training method, distance-based l…
Consistency Regularization for Generative Adversarial Networks
Han Zhang, Zizhao Zhang, Augustus Odena +1
Generative Adversarial Networks (GANs) are known to be difficult to train, despite considerable research effort. Several regularization techniques for stabilizing training have bee…
Consistency-based Semi-supervised Active Learning: Towards Minimizing Labeling Cost
Mingfei Gao, Zizhao Zhang, Guo Yu +3
Active learning (AL) combines data labeling and model training to minimize the labeling cost by prioritizing the selection of high value data that can best improve model performanc…
Distilling Effective Supervision from Severe Label Noise
Zizhao Zhang, Han Zhang, Sercan O. Arik +2
Collecting large-scale data with clean labels for supervised training of neural networks is practically challenging. Although noisy labels are usually cheap to acquire, existing me…
Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition
Zizhao Zhang, Adriana Romero, Matthew J. Muckley +3
The goal of MRI reconstruction is to restore a high fidelity image from partially observed measurements. This partial view naturally induces reconstruction uncertainty that can onl…