I explore whether humans and artificial neural networks are similar or different in how they perform on different category structures. I find that humans and …
Available here is the PERSEUS full Original .json dataset of 12 months, de-identified continuous data. Please read the PERSEUS Program Disseminated Dataset Descriptions and Use …
Technical paper published at SIGGRAPH Asia 2020. Paper abtsract: Manually authoring 3D shapes is difficult and time consuming; generative models of 3D shapes offer compelling …
The human brain and convolutional neural networks make similarity judgements in different ways when categorizing objects. Our project focuses in on improving the correspondence between …
The human brain and convolutional neural networks make similarity judgements in different ways when categorizing objects. Our project focuses in on improving the correspondence between …
Stroke is a leading cause of long-term disability, and outcome in regaining functionality in areas supplied by large vessel is directly related to timely endovascular …
Files associated with DOI:10.5281/zenodo.20636. Amp provides a modular approach to atomistic machine learning. The user can custom specify fingerprinting schemes and regression methods to suit …
Files associated with https://doi.org/10.1016/j.cpc.2016.05.010 and https://doi.org/10.5281/zenodo.46737. #Amp: Atomistic Machine-learning Potentials# Developed by Andrew Peterson & Alireza Khorshidi, Brown University School of Engineering. *Amp* allows for …
Files associated with https://doi.org/10.5281/zenodo.322427. Amp is an open-source package designed to easily bring machine-learning to atomistic calculations. This project is being developed at Brown University …
Files associated with https://doi.org/10.5281/zenodo.836788. Amp is an open-source package designed to easily bring machine-learning to atomistic calculations. This project is being developed at Brown University …
Adjudicated / Annotated Telemetry signals for Medically Important and Clinically Significant events-1 (ATOMICS-1) dataset. Derivation dataset with clinician-adjudicated red alarms [~8,530 datastream minutes over 853 …
Adjudicated / Annotated Telemetry signals for Medically Important and Clinically Significant events-1 (ATOMICS-1) dataset. Derivation dataset with clinician-adjudicated red alarms [~8,530 datastream minutes over 853 …
Adjudicated / Annotated Telemetry signals for Medically Important and Clinically Significant events-1 (ATOMICS-1) dataset. Derivation dataset with clinician-adjudicated red alarms [~8,530 datastream minutes over 853 …
