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Likelihood Landscapes: A Unifying Principle Behind Many Adversarial Defenses., , , , and . ECCV Workshops (1), volume 12535 of Lecture Notes in Computer Science, page 39-54. Springer, (2020)VisDA: A Synthetic-to-Real Benchmark for Visual Domain Adaptation., , , , , and . CVPR Workshops, page 2021-2026. Computer Vision Foundation / IEEE Computer Society, (2018)VIsCUIT: Visual Auditor for Bias in CNN Image Classifier., , , and . CVPR, page 21443-21451. IEEE, (2022)Adapting to Continuously Shifting Domains., , , and . ICLR (Workshop), OpenReview.net, (2018)Masked reconstruction based self-supervision for human activity recognition., , , , , , and . ISWC, page 45-49. ACM, (2020)S4T: Source-free domain adaptation for semantic segmentation via self-supervised selective self-training., , , and . CoRR, (2021)Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting., , , , , , , and . CoRR, (2023)RobustNav: Towards Benchmarking Robustness in Embodied Navigation., , , and . ICCV, page 15671-15680. IEEE, (2021)SENTRY: Selective Entropy Optimization via Committee Consistency for Unsupervised Domain Adaptation., , , and . ICCV, page 8538-8547. IEEE, (2021)Active Domain Adaptation via Clustering Uncertainty-weighted Embeddings., , , and . ICCV, page 8485-8494. IEEE, (2021)