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In recent years, generative diffusion models have achieved a rapid paradigm shift in deep generative models by showing groundbreaking performance across various applications.
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Cristóbal Esteban, Stephanie L Hyland, and Gunnar Rätsch · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Jinsung Yoon, James Jordon, and Mihaela Schaar · 2018
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Wei Cao, Dong Wang, Jian Li, Hao Zhou, Lei Li, and Yitan Li · 2018
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Hyunjik Kim and Andriy Mnih · 2018
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Variational autoencoders for collaborative filtering
Dawen Liang, Rahul G Krishnan, Matthew D Hoffman, and Tony Jebara · 2018
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Table-to-text generation by structure-aware seq2seq learning
Tianyu Liu, Kexiang Wang, Lei Sha, Baobao Chang, and Zhifang Sui · 2018
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Deep interest evolution network for click-through rate prediction
Guorui Zhou, Na Mou, Ying Fan, Qi Pi, Weijie Bian, Chang Zhou, Xiaoqiang Zhu, and Kun Gai · 2019
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Comparison of machine learning algorithms for clinical event prediction (risk of coronary heart disease)
Juan-Jose Beunza, Enrique Puertas, Ester García-Ovejero, Gema Villalba, Emilia Condes, Gergana Koleva, Cristian Hurtado, and Manuel F Landecho · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Modeling tabular data using conditional gan
Lei Xu, Maria Skoularidou, Alfredo Cuesta-Infante, and Kalyan Veeramachaneni · 2019
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Improving missing data imputation with deep generative models
Ramiro D Camino, Christian A Hammerschmidt, and Radu State · 2019
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Saeed Saremi and Aapo Hyvarinen · 2019
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Clinical requirements of future patient monitoring in the intensive care unit: qualitative study
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Synthesizing electronic health records using improved generative adversarial networks
Mrinal Kanti Baowaly, Chia-Ching Lin, Chao-Lin Liu, and Kuan-Ta Chen · 2019
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Synthesis of realistic ecg using generative adversarial networks
Anne Marie Delaney, Eoin Brophy, and Tomas E Ward · 2019
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Arcface: Additive angular margin loss for deep face recognition
Jiankang Deng, Jia Guo, Niannan Xue, and Stefanos Zafeiriou · 2019
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Bert4rec: Sequential recommendation with bidirectional encoder representations from transformer
Fei Sun, Jun Liu, Jian Wu, Changhua Pei, Xiao Lin, Wenwu Ou, and Peng Jiang · 2019
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Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
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Generating privacy-preserving synthetic tabular data using oblivious variational autoencoders
L Vivek Harsha Vardhan and Stanley Kok · 2020
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Quant gans: deep generation of financial time series
Magnus Wiese, Robert Knobloch, Ralf Korn, and Peter Kretschmer · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2020
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Sliced score matching: A scalable approach to density and score estimation
Yang Song, Sahaj Garg, Jiaxin Shi, and Stefano Ermon · 2020
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Diffwave: A versatile diffusion model for audio synthesis
Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, and Bryan Catanzaro · 2020
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Nvae: A deep hierarchical variational autoencoder
Arash Vahdat and Jan Kautz · 2020
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Diffusion models: A comprehensive survey of methods and applications
Ling Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Yingxia Shao, Wentao Zhang, Bin Cui, and Ming-Hsuan Yang · 2022
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A survey on generative diffusion model
Hanqun Cao, Cheng Tan, Zhangyang Gao, Guangyong Chen, Pheng-Ann Heng, and Stan Z Li · 2022
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Digress: Discrete denoising diffusion for graph generation
Clement Vignac, Igor Krawczuk, Antoine Siraudin, Bohan Wang, Volkan Cevher, and Pascal Frossard · 2022
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Tabddpm: Modelling tabular data with diffusion models
Akim Kotelnikov, Dmitry Baranchuk, Ivan Rubachev, and Artem Babenko · 2022
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Review of noise removal techniques in ecg signals
Shubhojeet Chatterjee, Rini Smita Thakur, Ram Narayan Yadav, Lalita Gupta, and Deepak Kumar Raghuvanshi · 2020
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Sequential recommendation with self-attentive multi-adversarial network
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Forecasting stock index price using the ceemdan-lstm model
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Credit card fraud detection using machine learning: a study
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Solving inverse problems in medical imaging with score-based generative models
Yang Song, Liyue Shen, Lei Xing, and Stefano Ermon · 2021
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Stasy: Score-based tabular data synthesis
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Diffusion models for missing value imputation in tabular data
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Diffusion-based time series imputation and forecasting with structured state space models
Juan Miguel Lopez Alcaraz and Nils Strodthoff · 2022
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Modeling temporal data as continuous functions with process diffusion
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Generative time series forecasting with diffusion, denoise, and disentanglement
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Recommendation via collaborative diffusion generative model
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Analog bits: Generating discrete data using diffusion models with self-conditioning
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Legal and ethical consideration in artificial intelligence in healthcare: who takes responsibility?
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Elucidating the design space of diffusion-based generative models
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Tackling the generative learning trilemma with denoising diffusion GANs
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Interpretability and fairness evaluation of deep learning models on mimic-iv dataset
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Fusion of sequential visits and medical ontology for mortality prediction
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Diffusion posterior sampling for general noisy inverse problems
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