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Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows) have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction mode   ...more

BACKGROUND: Neuromodulation devices have the potential to transform modern day treatments for patients with medicine-resistant neurological disease. For instance, the NeuroPace System (NeuroPace Inc, Mountain View, California) is a Food and Drug Administration (FDA)-approved device developed for closed-loop direct brain neurostimulation in the set   ...more

We present the formally verified predicate and strategy used to independently evaluate the safety of the final version (Run 15) of the FAAs next-generation air-traffic collision avoidance system, ACAS X. This approach is a general one that can analyze simultaneous vertical and horizontal maneuvers issued by aircraft collision avoidance systems. Th   ...more

We examine hierarchical approaches to image classification problems that include categories for which we have no training examples. Building on prior work in hierarchical classification that optimizes the trade-off between depth in a tree and accuracy of placement, we compare the performance of multiple formulations of the problem on both previous   ...more

Our objective was to compare the effectiveness of applying the historical limits method (HLM) to poison center (PC) call volumes with vs without stratifying by exposure type.   ...more

This work leverages Deep Reinforcement Learning (DRL) to make robotic control immune to changes in the robot manipulator or the environment and to perform reaching, collision avoidance and grasping without explicit, prior and fine knowledge of the human arm structure and kinematics, without careful hand-eye calibration, solely based on visual/reti   ...more

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