PPT-Machine Learning Classification for Rapid CAD-to-Simulation

Steven Owen Corey Ernst Armida Carbajal Matthew Peterson July 25 2022 Sandia Machine Learning and Deep Learning Workshop July 2528 2022 Albuquerque NM SAND20222014C Machine Learning Classification for Rapid CADtoSimulation. 1. Li-C. Wang. , . Malgorzata. . Marek-. Sadowska. University . of California, Santa Barbara. Synopsis. Simulation is a popular approach employed in many EDA applications. In this work, we explore the potential of using machine learning to improve simulation efficiency. Raman Sankaran. Saneem. Ahmed. Chandrahas. . Dewangan. . Sachin. . Nagargoje. Disclaimer. Most of the images in this presentation are shamelessly downloaded from Google images. Why is this pic included here ?. COS 116, Spring . 2012. Adam Finkelstein. Artificial Intelligence. Definition of AI (Merriam-Webster):. The capability of a machine to imitate intelligent human behavior. Branch of computer science dealing with the simulation of intelligent behavior in computers. scikit. -learn. http://scikit-learn.org/stable/. scikit. -learn. Machine Learning in Python. Simple . and efficient tools for data mining and data analysis. Built . on . NumPy. , . SciPy. , and . matplotlib. CS539. Prof. Carolina Ruiz. Department of Computer Science . (CS). & Bioinformatics and Computational Biology (BCB) Program. & Data Science (DS) Program. WPI. Most figures and images in this presentation were obtained from Google Images. Jianfu Chen. Computer Science Department. Stony Brook University. Machine learning learns an idealized model of the . real . world..  .  .  .  . 1 + 1 = 2.  .  . ?. Prod1 -> class1. 1. Sandia . National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of  Sandia, LLC, a wholly owned subsidiary of Honeywell International,  Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.  SAND2017-6417C. 01/24/2012. Agenda. 0. Introduction of machine . learning. --Some clinical examples. Introduction . of classification. 1. Cross validation. 2. . Over-fitting. Feature (gene) selection. Performance assessment. Classification of Transposable Elements . using a Machine . Learning Approach. Introduction. Transposable Elements (TEs) or jumping genes . are DNA . sequences that . have an intrinsic . capability to move within a host genome from one genomic location . Avdesh. Mishra, . Manisha. . Panta. , . Md. . Tamjidul. . Hoque. , Joel . Atallah. Computer Science and Biological Sciences Department, University of New Orleans. Presentation Overview. 4/10/2018. Linking historical administrative data. Context. History of very important contributions:. Dutch Famine Birth Cohort Study – epigenetics, thrifty phenotype. Överkalix. study – epigenetics, sex differences. Dr. Alex Vakanski. Lecture . 10. AML in . Cybersecurity – Part I:. Malware Detection and Classification. . Lecture Outline. Machine Learning in cybersecurity. Adversarial Machine Learning in cybersecurity. Ryan Ma . Background and Purpose of the Project. Aerodynamic analysis is one of the most crucial traits of a vehicle. It affects the fuel consumption of a car. . The shape of the car significantly affects the aerodynamic performances, which includes the lift and the drag. . Er. . . Mohd. . Shah . Alam. Assistant Professor. Department of Computer Science & Engineering,. UIET, CSJM University, Kanpur. Agenda. What is Machine Learning?. How Machine learning . is differ from Traditional Programming?.