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An Empirical Investigation of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration., and . CoRR, (2023)No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths., , , and . CoRR, (2023)How Image Corruption and Perturbation Affect Out-of-Distribution Generalization and Calibration., and . IJCNN, page 1-6. IEEE, (2023)Conjugate Gradient Method for Generative Adversarial Networks., and . CoRR, (2022)Optimal Transport meets Noisy Label Robust Loss and MixUp Regularization for Domain Adaptation., , and . CoLLAs, volume 199 of Proceedings of Machine Learning Research, page 966-981. PMLR, (2022)Conjugate Gradient Method for Generative Adversarial Networks., and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 4381-4408. PMLR, (2023)A Performance Improvement Approach for Second-Order Optimization in Large Mini-batch Training., and . CCGRID, page 696-703. IEEE, (2019)Empirical Study on Optimizer Selection for Out-of-Distribution Generalization., , , , , , , and . CoRR, (2022)Towards Understanding Variants of Invariant Risk Minimization through the Lens of Calibration., and . CoRR, (2024)Story-to-Images Translation: Leveraging Diffusion Models and Large Language Models for Sequence Image Generation., , and . NarSUM@MM, page 57-63. ACM, (2023)