Results 21 to 30 of about 22,229,619 (357)
A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection [PDF]
IEEE International Conference on Computer Vision, 2021 Anomaly detection, the task of identifying unusual samples in data, often relies on a large set of training samples. In this work, we consider the setting of few-shot anomaly detection in images, where only a few images are given at training. We devise a
Shelly Sheynin, Sagie Benaim, Lior Wolf
semanticscholar +1 more source
StylePeople: A Generative Model of Fullbody Human Avatars [PDF]
Computer Vision and Pattern Recognition, 2021 We propose a new type of full-body human avatars, which combines parametric mesh-based body model with a neural texture. We show that with the help of neural textures, such avatars can successfully model clothing and hair, which usually poses a problem ...
A. Grigorev +6 more
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RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment [PDF]
Trans. Mach. Learn. Res., 2023 Generative foundation models are susceptible to implicit biases that can arise from extensive unsupervised training data. Such biases can produce suboptimal samples, skewed outcomes, and unfairness, with potentially serious consequences.
Hanze Dong +7 more
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Generative Model based Highly Efficient Semantic Communication Approach for Image Transmission [PDF]
IEEE International Conference on Acoustics, Speech, and Signal Processing, 2022 Deep learning (DL) based semantic communication methods have been explored to transmit images efficiently in recent years. In this paper, we propose a generative model based semantic communication to further improve the efficiency of image transmission ...
Tian Han +5 more
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EffUnet-SpaGen: An Efficient and Spatial Generative Approach to Glaucoma Detection
Journal of Imaging, 2021 Current research in automated disease detection focuses on making algorithms “slimmer” reducing the need for large training datasets and accelerating recalibration for new data while achieving high accuracy. The development of slimmer models has become a
Venkatesh Krishna Adithya +7 more
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MultiVI: deep generative model for the integration of multimodal data
Nature Methods, 2023 By learning a joint representation using deep generative modeling, MultiVI integrates multimodal and single-modality single-cell datasets, which enhances multiple functionalities.
Tal Ashuach +5 more
semanticscholar +1 more source
Frontiers in Artificial Intelligence, 2020 The Free Energy Principle and Active Inference Framework (FEP-AI) begins with the understanding that persisting systems must regulate environmental exchanges and prevent entropic accumulation.
Adam Safron
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Generalized Thirring Models [PDF]
Annals of Physics, 1996 LaTex 55 pages, 2 figures, extended version of our previous work (hep-th/9308067)
Sachs, I., Wipf, A.
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SinGAN: Learning a Generative Model From a Single Natural Image [PDF]
IEEE International Conference on Computer Vision, 2019 We introduce SinGAN, an unconditional generative model that can be learned from a single natural image. Our model is trained to capture the internal distribution of patches within the image, and is then able to generate high quality, diverse samples that
Tamar Rott Shaham +2 more
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An all-atom protein generative model
bioRxiv, 2023 Proteins mediate their functions through chemical interactions; modeling these interactions, which are typically through sidechains, is an important need in protein design. However, constructing an all-atom generative model requires an appropriate scheme
Alexander E. Chu +4 more
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