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SSRN Electronic JournalGenerativeAI (GenAI) is a buzz term in the field of Artificial Intelligence (AI). It is a branch of AI, which has the capability to create content in various forms such as text, audio and video, by leveraging patterns in existing data. GenAI utilizes variety of Machine Learning and Deep Learning algorithms.
Thumala Srinivasa Rao +4 more
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International Journal of Advanced Engineering and Nano Technology, 2023 Recent advancements in generative artificial intelligence (AI) have made it possible for machines to independently produce a variety of creative content. In the context of producing creative content, this essay examines the developments, difficulties, and ethical issues relating to generative AI.
Stefan Feuerriegel +3 more
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Deep Generative Modeling of LiDAR Data [PDF]
, 2019 Building models capable of generating structured output is a key challenge for AI and robotics. While generative models have been explored on many types of data, little work has been done on synthesizing lidar scans, which play a key role in robot ...
Caccia, Lucas +3 more
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A hybrid generative/discriminative framework to train a semantic parser from an un-annotated corpus [PDF]
, 2008 We propose a hybrid generative/discriminative framework for semantic parsing which combines the hidden vector state (HVS) model and the hidden Markov support vector machines (HMSVMs).
He, Yulan, Zhou, Deyu
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Synthetic-Neuroscore: Using A Neuro-AI Interface for Evaluating Generative Adversarial Networks
, 2020 Generative adversarial networks (GANs) are increasingly attracting attention in the computer vision, natural language processing, speech synthesis and similar domains. Arguably the most striking results have been in the area of image synthesis.
Healy, Graham +4 more
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Differentially Private Mixture of Generative Neural Networks [PDF]
, 2017 Generative models are used in a wide range of applications building on large amounts of contextually rich information. Due to possible privacy violations of the individuals whose data is used to train these models, however, publishing or sharing ...
Acs, Gergely +3 more
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Building Machines That Learn and Think Like People [PDF]
, 2016 Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video games, and ...
Gershman, Samuel J. +3 more
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Adversarial Training in Affective Computing and Sentiment Analysis: Recent Advances and Perspectives [PDF]
, 2018 Over the past few years, adversarial training has become an extremely active research topic and has been successfully applied to various Artificial Intelligence (AI) domains.
Cummins, Nicholas +3 more
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Adversarial Learned Molecular Graph Inference and Generation
, 2020 Recent methods for generating novel molecules use graph representations of molecules and employ various forms of graph convolutional neural networks for inference.
Pölsterl, Sebastian +1 more
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Clustering with Spectral Norm and the k-means Algorithm [PDF]
, 2010 There has been much progress on efficient algorithms for clustering data points generated by a mixture of $k$ probability distributions under the assumption that the means of the distributions are well-separated, i.e., the distance between the means of ...
Kannan, Ravindran, Kumar, Amit
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