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Wearables and Deep Learning Classify Fall Risk From Gait in Multiple Sclerosis.

, , , , , , , , and . IEEE J. Biomed. Health Informatics, 25 (5): 1824-1831 (2021)

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The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities, , , , , , , , , and 42 other author(s). (2018)cite arxiv:1803.03453.Reset It and Forget It: Relearning Last-Layer Weights Improves Continual and Transfer Learning., , , and . CoRR, (2023)The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities., , , , , , , , , and 43 other author(s). CoRR, (2018)How Much Data Is Enough? A Reliable Methodology to Examine Long-Term Wearable Data Acquisition in Gait and Postural Sway., , , , , , , , , and 4 other author(s). Sensors, 22 (18): 6982 (2022)Editorial: Evolving Robotic Morphologies., , and . Frontiers Robotics AI, (2022)The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities., , , , , , , , , and 43 other author(s). Artif. Life, 26 (2): 274-306 (2020)Interoceptive robustness through environment-mediated morphological development., , , and . GECCO, page 109-116. ACM, (2018)The ChAMP App: A Scalable mHealth Technology for Detecting Digital Phenotypes of Early Childhood Mental Health., , , , , , , , , and 1 other author(s). IEEE J. Biomed. Health Informatics, 28 (4): 2304-2313 (April 2024)Evolving swimming soft-bodied creatures, , , , and . 15th International Conference on the Synthesis and Simulation of Living Systems (ALIFE XV), page 6. (2016)Simulating the evolution of soft and rigid-body robots., , , , , and . GECCO (Companion), page 1117-1120. ACM, (2017)