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Scale-Equivariant Unrolled Neural Networks for Data-Efficient Accelerated MRI Reconstruction., , , , , , и . MICCAI (6), том 13436 из Lecture Notes in Computer Science, стр. 737-747. Springer, (2022)Hidden Convexity of Wasserstein GANs: Interpretable Generative Models with Closed-Form Solutions., , , , , , и . ICLR, OpenReview.net, (2022)Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization., , , , , и . ICLR, OpenReview.net, (2022)Vector-output ReLU Neural Network Problems are Copositive Programs: Convex Analysis of Two Layer Networks and Polynomial-time Algorithms., , , и . CoRR, (2020)Convex Regularization Behind Neural Reconstruction., , , , и . CoRR, (2020)GLEAM: Greedy Learning for Large-Scale Accelerated MRI Reconstruction., , , , , , , , и . CoRR, (2022)In situ width estimation of biofuel plant stems., , , и . Computational Imaging, Society for Imaging Science and Technology, (2019)Scaling Convex Neural Networks with Burer-Monteiro Factorization., , , , , и . ICLR, OpenReview.net, (2024)Convex Regularization behind Neural Reconstruction., , , , и . ICLR, OpenReview.net, (2021)Vector-output ReLU Neural Network Problems are Copositive Programs: Convex Analysis of Two Layer Networks and Polynomial-time Algorithms., , , и . ICLR, OpenReview.net, (2021)