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Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders., , and . CoRR, (2021)Bayesian Active Learning for Scanning Probe Microscopy: from Gaussian Processes to Hypothesis Learning., , , , and . CoRR, (2022)Deep Learning for Automated Experimentation in Scanning Transmission Electron Microscopy., , , , , , , , , and 2 other author(s). CoRR, (2023)Discovery of structure-property relations for molecules via hypothesis-driven active learning over the chemical space., , and . CoRR, (2023)Optimizing training trajectories in variational autoencoders via latent Bayesian optimization approach *., , , and . Mach. Learn. Sci. Technol., 4 (1): 15011 (March 2023)Towards automating structural discovery in scanning transmission electron microscopy *., , , , and . Mach. Learn. Sci. Technol., 3 (1): 15024 (2022)Robust Feature Disentanglement in Imaging Data via Joint Invariant Variational Autoencoders: from Cards to Atoms., and . CoRR, (2021)Exploring the Evolution of Metal Halide Perovskites via Latent Representations of the Photoluminescent Spectra., , , , , and . Adv. Intell. Syst., (May 2023)A dynamic Bayesian optimized active recommender system for curiosity-driven Human-in-the-loop automated experiments., , , , , , , , and . CoRR, (2023)Deep Kernel Methods Learn Better: From Cards to Process Optimization., , , and . CoRR, (2023)