S19-208 Improved Anomaly Detection Using Adversarially Learned Inference Researchers at Stanford have developed a potentially best-in-class anomaly detection method with a wide range of applications. Ziyi Yang Eric Darve Iman Soltani Bozchalooi
S19-165 Trainable Analog Hardware Platform for Recurrent Neural Networks (RNN) Machine learning models currently require extensive computational resources and this demand is growing rapidly with new models and applications being introduced. Tyler Hughes Ian Williamson Momchil Minkov Shanhui Fan