PPT-Generative Models

vs Discriminative models Roughly Discriminative Feedforw ard Bottomup Generative Feedforward recurrent feedback Bottomup horizontal topdown Compositional generative models require a flexible universal representation format for relationships. This has led to various proposals for sampling from this implicitly learned density function using Langevin and MetropolisHastings MCMC However it remained unclear how to connect the training procedure of regularized autoencoders to the implicit est ponentvectorkandiindexesintothevocabu-lary.Azero-meanLaplacepriorhasthesameef-fectasplacinganL1regularizeronki,inducingsparsitywhileatthesametimepermittingmoreex-tremedeviationsfromthemean.TheLaplac approaches to alternations LING 451/551 Spring 2011 Generative view of phonology • Hayes 6.1.1 – ‘The morphology of  lnguge plces morphemes in dif etc. Convnets. (optimize weights to predict bus). bus. Convnets. (optimize input to predict ostrich). ostrich. Work on Adversarial examples by . Goodfellow. et al. , . Szegedy. et. al., etc.. Generative Adversarial Networks (GAN) [. Part-based models. Many slides adapted from Fei-Fei Li, Rob Fergus, and Antonio Torralba. Implicit shape models. Visual codebook is used to index votes for object position. B. Leibe, A. Leonardis, and B. Schiele, . Nets. İlke Çuğu 1881739. NIPS 2014 . Ian. . Goodfellow. et al.. At a . glance. (. http://www.kdnuggets.com/2017/01/generative-adversarial-networks-hot-topic-machine-learning.html. ). Idea. . Behind. November 27 | . 2015. Facilitator. Mark Friesen. Consulting Manager, . Vantage Point. mfriesen@thevantagepoint.ca. @. markalanfriesen. Agenda. Introductions. Board Fundamentals | Organization Name. Governance. Carilion. Research Institute. Bradley Department of Electrical & Computer Engineering. Department of Psychiatry and . Behavioral. Medicine, VTC School of Medicine. Dynamic Causal . Modelling. . Erdős-Rényi. Random model, . Watts-. Strogatz. Small-world, . Barabási. -Albert Preferential attachment, . Molloy-Reed . Configuration model . and . Gilbert . Random . G. eometric model. Excellence Through Knowledge. Akrit Mohapatra. ECE Department, Virginia Tech. What are GANs?. System of . two neural networks competing against each other in a zero-sum game framework. . They were first introduced by . Ian Goodfellow. An Overview. Yidong. Chai. 1,2. , . Weifeng Li. 1,3. , Hsinchun Chen. 1. 1 . Artificial Intelligence Laboratory, The University of Arizona. 2 . Tsinghua University. 3 . University of Georgia. 1. Acknowledgements. ). Prof. . Ralucca Gera, . Applied Mathematics Dept.. Naval Postgraduate School. Monterey, California. rgera@nps.edu. Excellence Through Knowledge. Learning Outcomes. I. dentify . network models and explain their structures. Nisheeth. Coin toss example. Say you toss a coin N times. You want to figure out its bias. Bayesian approach. Find the generative model. Each toss ~ Bern(. θ. ). θ. ~ Beta(. α. ,. β. ). Draw the generative model in plate notation. Fall 2023. What is Generative AI?. ChatGPT, Bing, Bard, . DallE. …. Generative AI, like ChatGPT, uses machine learning to create new content. While generative AI tools can help explore new ideas, write text, and get feedback, there are important limitations to these tools to keep in mind..