Explainability and the Inexplicable In episode six of season four we chat about AI and religion, we take a listener question about personal bias checking and we hear from Been Kim of Google Brain. See More Episodes arXiv Whitepapers A Patterns Based Approach for Design of Educational Technologies. Instructional design is a fundamental base for educational technologies as itlays the foundation to facilitate learning and teaching based on pedagogicalunderpinnings. However, most of the educational technologies today face twocore challenges in this context: (i) lack of instructional design as a... Random Features for Large-Scale Kernel Machines To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The features are designed so that the inner products of the transformed data are approximately equal to those in the feature... Learning the Base Distribution in Implicit Generative Models. Popular generative model learning methods such as Generative Adversarial Networks (GANs), and Variational Autoencoders (VAE) enforce the latent representation to follow simple distributions such as isotropic Gaussian. In this paper, we argue that learning a complicated distribution over the latent... More featured content News Articles Artificial intelligence suggests recipes based on food photos Lincoln Laboratory enters licensing agreement to produce its localizing ground-penetrating radar Stay in the loop. Subscribe to our newsletter for a weekly update on the latest podcast, news, events, and jobs postings. E-mail Bringing neural networks to cellphones Miniaturizing the brain of a drone Computer system predicts products of chemical reactions Measuring biological dust in the wind Shrinking data for surgical training Armando Solar-Lezama: Academic success despite an inauspicious start Explained: Neural networks Looking ahead to the future of computer-driven cars More news