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Diffusion models have been widely used in time series and spatio-temporal data, enhancing generative, inferential, and downstream capabilities.
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The National Sleep Research Resource: towards a sleep data commons
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Adversarial Audio Synthesis. In International Conference on Learning Representations
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Attention based spatial-temporal graph convolutional networks for traffic flow forecasting. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 33. 922–929
Shengnan Guo, Youfang Lin, Ning Feng, Chao Song, and Huaiyu Wan. 2019 · 2019
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Multitask learning and benchmarking with clinical time series data
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ACN-data: Analysis and applications of an open EV charging dataset. In Proceedings of the tenth ACM international conference on future energy systems . 139–149
Zachary J Lee, Tongxin Li, and Steven H Low. 2019 · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon. 2019 · 2019
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Wavegrad: Estimating gradients for waveform generation
Nanxin Chen, Yu Zhang, Heiga Zen, Ron J Weiss, Mohammad Norouzi, and William Chan. 2020 · 2020
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PFST-LSTM: A SpatioTemporal LSTM Model With Pseudoflow Prediction for Precipitation Nowcasting
Luo Chuyao, Xutao Li, and Yunming Ye. 2020 · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020 · 2020
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Solving linear inverse problems using the prior implicit in a denoiser
Zahra Kadkhodaie and Eero P Simoncelli. 2020 · 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 · 2020
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IPSL-CM5A2–an Earth system model designed for multi-millennial climate simulations
Pierre Sepulchre, Arnaud Caubel, Jean-Baptiste Ladant, Laurent Bopp, Olivier Boucher, Pascale Braconnot, Patrick Brockmann, Anne Cozic, Yannick Donnadieu, Jean-Louis Dufresne, et al · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon. 2020a · 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. 2020b · 2020
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Predicting citywide crowd flows in irregular regions using multi-view graph convolutional networks
Junkai Sun, Junbo Zhang, Qiaofei Li, Xiuwen Yi, Yuxuan Liang, and Yu Zheng. 2020 · 2020
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Segdiff: Image segmentation with diffusion probabilistic models
Tomer Amit, Tal Shaharbany, Eliya Nachmani, and Lior Wolf. 2021 · 2021
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Structured denoising diffusion models in discrete state-spaces
Jacob Austin, Daniel D Johnson, Jonathan Ho, Daniel Tarlow, and Rianne Van Den Berg. 2021 · 2021
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Label-efficient semantic segmentation with diffusion models
Dmitry Baranchuk, Ivan Rubachev, Andrey Voynov, Valentin Khrulkov, and Artem Babenko. 2021 · 2021
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Ilvr: Conditioning method for denoising diffusion probabilistic models
Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, and Sungroh Yoon. 2021 · 2021
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Minirocket: A very fast (almost) deterministic transform for time series classification. In Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data mining . 248–257
Angus Dempster, Daniel F Schmidt, and Geoffrey I Webb. 2021 · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol. 2021 · 2021
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Argmax flows and multinomial diffusion: Learning categorical distributions
Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, and Max Welling. 2021 · 2021
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A variational perspective on diffusion-based generative models and score matching
Chin-Wei Huang, Jae Hyun Lim, and Aaron C Courville. 2021 · 2021
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Gotta go fast when generating data with score-based models
Alexia Jolicoeur-Martineau, Ke Li, Rémi Piché-Taillefer, Tal Kachman, and Ioannis Mitliagkas. 2021 · 2021
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Variational diffusion models
Diederik Kingma, Tim Salimans, Ben Poole, and Jonathan Ho. 2021 · 2021
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On fast sampling of diffusion probabilistic models
Zhifeng Kong and Wei Ping. 2021 · 2021
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On generative spoken language modeling from raw audio
Kushal Lakhotia, Eugene Kharitonov, Wei-Ning Hsu, Yossi Adi, Adam Polyak, Benjamin Bolte, Tu-Anh Nguyen, Jade Copet, Alexei Baevski, Abdelrahman Mohamed, et al · 2021
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Fine-grained urban flow prediction. In Proceedings of the Web Conference 2021 . 1833–1845
Yuxuan Liang, Kun Ouyang, Junkai Sun, Yiwei Wang, Junbo Zhang, Yu Zheng, David Rosenblum, and Roger Zimmermann. 2021a · 2021
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Comparing recognition performance and robustness of multimodal deep learning models for multimodal emotion recognition
Wei Liu, Jie-Lin Qiu, Wei-Long Zheng, and Bao-Liang Lu. 2021b · 2021
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen. 2021 · 2021
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Improved denoising diffusion probabilistic models. In International Conference on Machine Learning . PMLR, 8162–8171
Alexander Quinn Nichol and Prafulla Dhariwal. 2021 · 2021
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Autoregressive denoising diffusion models for multivariate probabilistic time series forecasting. In International Conference on Machine Learning . PMLR, 8857–8868
Kashif Rasul, Calvin Seward, Ingmar Schuster, and Roland Vollgraf. 2021 · 2021
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High-Resolution Image Synthesis with Latent Diffusion Models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2021 · 2021
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Maximum likelihood training of score-based diffusion models
Yang Song, Conor Durkan, Iain Murray, and Stefano Ermon. 2021 · 2021
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Csdi: Conditional score-based diffusion models for probabilistic time series imputation
Yusuke Tashiro, Jiaming Song, Yang Song, and Stefano Ermon. 2021 · 2021
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Score-based generative modeling in latent space
Arash Vahdat, Karsten Kreis, and Jan Kautz. 2021 · 2021
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Learning to efficiently sample from diffusion probabilistic models
Daniel Watson, Jonathan Ho, Mohammad Norouzi, and William Chan. 2021 · 2021
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Tijin Yan, Hongwei Zhang, Tong Zhou, Yufeng Zhan, and Yuanqing Xia. 2021 · 2021
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Building normalizing flows with stochastic interpolants
Michael S Albergo and Eric Vanden-Eijnden. 2022 · 2022
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Diffusion-based time series imputation and forecasting with structured state space models
Juan Miguel Lopez Alcaraz and Nils Strodthoff. 2022 · 2022
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Cold diffusion: Inverting arbitrary image transforms without noise
Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie S Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, and Tom Goldstein. 2022 · 2022
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Why Are Conditional Generative Models Better Than Unconditional Ones?
Fan Bao, Chongxuan Li, Jiacheng Sun, and Jun Zhu. 2022 · 2022
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Modeling temporal data as continuous functions with process diffusion
Marin Biloš, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka, and Stephan Günnemann. 2022 · 2022
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Quasi-Conservative Score-based Generative Models
Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, and Chun-Yi Lee. 2022 · 2022
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Come-closer-diffuse-faster: Accelerating conditional diffusion models for inverse problems through stochastic contraction. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 12413–12422
Hyungjin Chung, Byeongsu Sim, and Jong Chul Ye. 2022 · 2022
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Soft diffusion: Score matching for general corruptions
Giannis Daras, Mauricio Delbracio, Hossein Talebi, Alexandros G Dimakis, and Peyman Milanfar. 2022 · 2022
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It’s Raw! Audio Generation with State-Space Models
Karan Goel, Albert Gu, Chris Donahue, and Christopher Ré. 2022 · 2022
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Diffuseq: Sequence to sequence text generation with diffusion models
Shansan Gong, Mukai Li, Jiangtao Feng, Zhiyong Wu, and LingPeng Kong. 2022 · 2022
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Vector quantized diffusion model for text-to-image synthesis. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 10696–10706
Shuyang Gu, Dong Chen, Jianmin Bao, Fang Wen, Bo Zhang, Dongdong Chen, Lu Yuan, and Baining Guo. 2022 · 2022
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Card: Classification and regression diffusion models
Xizewen Han, Huangjie Zheng, and Mingyuan Zhou. 2022 · 2022
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Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans. 2022 · 2022
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Video diffusion models
Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J Fleet. 2022 · 2022
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Emiel Hoogeboom and Tim Salimans. 2022 · 2022
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Time series anomaly detection by cumulative radon features
Yedid Hoshen. 2022 · 2022
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Global context with discrete diffusion in vector quantised modelling for image generation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 11502–11511
Minghui Hu, Yujie Wang, Tat-Jen Cham, Jianfei Yang, and Ponnuthurai N Suganthan. 2022 · 2022
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Fastdiff: A fast conditional diffusion model for high-quality speech synthesis
Rongjie Huang, Max WY Lam, Jun Wang, Dan Su, Dong Yu, Yi Ren, and Zhou Zhao. 2022 · 2022
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Elucidating the Design Space of Diffusion-Based Generative Models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine. 2022 · 2022
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Denoising diffusion restoration models
Bahjat Kawar, Michael Elad, Stefano Ermon, and Jiaming Song. 2022 · 2022
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Diffusion-lm improves controllable text generation
Xiang Li, John Thickstun, Ishaan Gulrajani, Percy S Liang, and Tatsunori B Hashimoto. 2022b · 2022
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Generative time series forecasting with diffusion, denoise, and disentanglement
Yan Li, Xinjiang Lu, Yaqing Wang, and Dejing Dou. 2022a · 2022
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Towards end-to-end unsupervised speech recognition. In 2022 IEEE Spoken Language Technology Workshop (SLT) . IEEE, 221–228
Alexander H Liu, Wei-Ning Hsu, Michael Auli, and Alexei Baevski. 2023b · 2022
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Pseudo numerical methods for diffusion models on manifolds
Luping Liu, Yi Ren, Zhijie Lin, and Zhou Zhao. 2022c · 2022
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Flow straight and fast: Learning to generate and transfer data with rectified flow
Xingchao Liu, Chengyue Gong, and Qiang Liu. 2022a · 2022
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Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu. 2022b · 2022
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Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu. 2022c · 2022
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Conditional diffusion probabilistic model for speech enhancement. In ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 7402–7406
Yen-Ju Lu, Zhong-Qiu Wang, Shinji Watanabe, Alexander Richard, Cheng Yu, and Yu Tsao. 2022a · 2022
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Repaint: Inpainting using denoising diffusion probabilistic models. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition . 11461–11471
Andreas Lugmayr, Martin Danelljan, Andres Romero, Fisher Yu, Radu Timofte, and Luc Van Gool. 2022 · 2022
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Accelerating diffusion models via early stop of the diffusion process
Zhaoyang Lyu, Xudong Xu, Ceyuan Yang, Dahua Lin, and Bo Dai. 2022 · 2022
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3d-ldm: Neural implicit 3d shape generation with latent diffusion models
Gimin Nam, Mariem Khlifi, Andrew Rodriguez, Alberto Tono, Linqi Zhou, and Paul Guerrero. 2022 · 2022
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Diffusevae: Efficient, controllable and high-fidelity generation from low-dimensional latents
Kushagra Pandey, Avideep Mukherjee, Piyush Rai, and Abhishek Kumar. 2022 · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen. 2022 · 2022
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Generative modelling with inverse heat dissipation
Severi Rissanen, Markus Heinonen, and Arno Solin. 2022 · 2022
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High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition . 10684–10695
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2022 · 2022
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Palette: Image-to-image diffusion models. In ACM SIGGRAPH 2022 conference proceedings . 1–10
Chitwan Saharia, William Chan, Huiwen Chang, Chris Lee, Jonathan Ho, Tim Salimans, David Fleet, and Mohammad Norouzi. 2022a · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
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Image super-resolution via iterative refinement
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J Fleet, and Mohammad Norouzi. 2022c · 2022
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Structure-based drug design with equivariant diffusion models
Arne Schneuing, Yuanqi Du, Charles Harris, Arian Jamasb, Ilia Igashov, Weitao Du, Tom Blundell, Pietro Lió, Carla Gomes, Max Welling, et al · 2022
Cited alongside, same era.
Universal speech enhancement with score-based diffusion
Joan Serrà, Santiago Pascual, Jordi Pons, R Oguz Araz, and Davide Scaini. 2022 · 2022
Cited alongside, same era.
Dual diffusion implicit bridges for image-to-image translation
Xuan Su, Jiaming Song, Chenlin Meng, and Stefano Ermon. 2022 · 2022
Cited alongside, same era.
Lion: Latent point diffusion models for 3d shape generation
Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis, et al · 2022
Cited alongside, same era.
Speech enhancement with score-based generative models in the complex STFT domain
Diffstg: Probabilistic spatio-temporal graph forecasting with denoising diffusion models. In Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems . 1–12
Haomin Wen, Youfang Lin, Yutong Xia, Huaiyu Wan, Qingsong Wen, Roger Zimmermann, and Yuxuan Liang. 2023 · 2023
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Next-gpt: Any-to-any multimodal llm
Shengqiong Wu, Hao Fei, Leigang Qu, Wei Ji, and Tat-Seng Chua. 2023 · 2023
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Imputation-based Time-Series Anomaly Detection with Conditional Weight-Incremental Diffusion Models. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining . 2742–2751
Chunjing Xiao, Zehua Gou, Wenxin Tai, Kunpeng Zhang, and Fan Zhou. 2023 · 2023
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Restart sampling for improving generative processes
Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, and Tommi Jaakkola. 2023a · 2023
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Simon Welker, Julius Richter, and Timo Gerkmann. 2022 · 2022
Cited alongside, same era.
Anomaly detection in multi-agent trajectories for automated driving. In Conference on Robot Learning . PMLR, 1223–1233
Julian Wiederer, Arij Bouazizi, Marco Troina, Ulrich Kressel, and Vasileios Belagiannis. 2022 · 2022
Cited alongside, same era.
Geodiff: A geometric diffusion model for molecular conformation generation
Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, and Jian Tang. 2022b · 2022
Cited alongside, same era.
Poisson Flow Generative Models
Yilun Xu, Ziming Liu, Max Tegmark, and T. Jaakkola. 2022a · 2022
Cited alongside, same era.
Score-Based Graph Generative Modeling with Self-Guided Latent Diffusion
Ling Yang, Zhilong Zhang, Wentao Zhang, and Shenda Hong. 2022 · 2022
Cited alongside, same era.
Fast sampling of diffusion models with exponential integrator
Qinsheng Zhang and Yongxin Chen. 2022 · 2022
Cited alongside, same era.
gddim: Generalized denoising diffusion implicit models
Qinsheng Zhang, Molei Tao, and Yongxin Chen. 2022 · 2022
Cited alongside, same era.
Truncated diffusion probabilistic models
Huangjie Zheng, Pengcheng He, Weizhu Chen, and Mingyuan Zhou. 2022 · 2022
Cited alongside, same era.
Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark, and T. Jaakkola. 2023b · 2023
Later among the works it cites.
A Short-Term Wind Power Scenario Generation Method Based on Conditional Diffusion Model. In 2023 IEEE Sustainable Power and Energy Conference (iSPEC) . IEEE, 1–6
Jinghao Yan, Pai Li, and Yuehui Huang. 2023 · 2023
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DDMT: Denoising Diffusion Mask Transformer Models for Multivariate Time Series Anomaly Detection
Chaocheng Yang, Tingyin Wang, and Xuanhui Yan. 2023b · 2023
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Diffsound: Discrete diffusion model for text-to-sound generation
Dongchao Yang, Jianwei Yu, Helin Wang, Wen Wang, Chao Weng, Yuexian Zou, and Dong Yu. 2023d · 2023
Later among the works it cites.
Diffusion models: A comprehensive survey of methods and applications
Ling Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Wentao Zhang, Bin Cui, and Ming-Hsuan Yang. 2023e · 2023
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Diffusion probabilistic modeling for video generation
Ruihan Yang, Prakhar Srivastava, and Stephan Mandt. 2023a · 2023
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A Graph-Based Scene Encoder for Vehicle Trajectory Prediction Using the Diffusion Model. In 2023 International Annual Conference on Complex Systems and Intelligent Science (CSIS-IAC) . 981–986
Yueyang Yao, Yahui Liu, Xingyuan Dai, Shichao Chen, and Yisheng Lv. 2023a · 2023
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A Graph-Based Scene Encoder for Vehicle Trajectory Prediction Using the Diffusion Model. In 2023 International Annual Conference on Complex Systems and Intelligent Science (CSIS-IAC) . IEEE, 981–986
Yueyang Yao, Yahui Liu, Xingyuan Dai, Shichao Chen, and Yisheng Lv. 2023b · 2023
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Haiming Yi, Lei Hou, Yuhong Jin, and Nasser A Saeed. 2023 · 2023
Later among the works it cites.
EHRDiff: Exploring Realistic EHR Synthesis with Diffusion Models
Hongyi Yuan, Songchi Zhou, and Sheng Yu. 2023c · 2023
Later among the works it cites.
Spatio-temporal Diffusion Point Processes
Yuan Yuan, Jingtao Ding, Chenyang Shao, Depeng Jin, and Yong Li. 2023a · 2023
Later among the works it cites.
Imputation as Inpainting: Diffusion models for SpatioTemporal Data Imputation
Taeyoung Yun, Haewon Jung, and Jiwoo Son. 2023 · 2023
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Fast Diffusion GAN Model for Symbolic Music Generation Controlled by Emotions
Jincheng Zhang, György Fazekas, and Charalampos Saitis. 2023a · 2023
Later among the works it cites.
sasdim: self-adaptive noise scaling diffusion model for spatial time series imputation
Shunyang Zhang, Senzhang Wang, Xianzhen Tan, Ruochen Liu, Jian Zhang, and Jianxin Wang. 2023d · 2023
Later among the works it cites.
Multi-scale conditional diffusion model for deposited droplet volume measurement in inkjet printing manufacturing
Zhou Zhang, Hua Yang, Jiankui Chen, and Zhouping Yin. 2023e · 2023
Later among the works it cites.
DiffUFlow: Robust Fine-grained Urban Flow Inference with Denoising Diffusion Model. In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management . 3505–3513
Yuhao Zheng, Lian Zhong, Senzhang Wang, Yu Yang, Weixi Gu, Junbo Zhang, and Jianxin Wang. 2023 · 2023
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Towards Graph-Aware Diffusion Modeling for Collaborative Filtering
Yunqin Zhu, Chao Wang, and Hui Xiong. 2023 · 2023
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Unsupervised Statistical Feature-Guided Diffusion Model for Sensor-based Human Activity Recognition
Si Zuo, Vitor Fortes Rey, Sungho Suh, Stephan Sigg, and Paul Lukowicz. 2023 · 2023
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Accurate structure prediction of biomolecular interactions with AlphaFold 3
Josh Abramson, Jonas Adler, Jack Dunger, Richard Evans, Tim Green, Alexander Pritzel, Olaf Ronneberger, Lindsay Willmore, Andrew J Ballard, Joshua Bambrick, et al · 2024
Closest in time.
A Transformer-based Diffusion Probabilistic Model for Heart Rate and Blood Pressure Forecasting in Intensive Care Unit
Ping Chang, Huayu Li, Stuart F Quan, Shuyang Lu, Shu-Fen Wung, Janet Roveda, and Ao Li. 2024 · 2024
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Online prediction of mechanical and electrical quality in ultrasonic metal welding using time series generation and deep learning
Honghuan Chen, Xin Dong, Yaguang Kong, Zhangping Chen, Song Zheng, Xiaoping Hu, and Xiaodong Zhao. 2024a · 2024
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Quantifying uncertainty: Air quality forecasting based on dynamic spatial-temporal denoising diffusion Probabilistic model
Kehua Chen, Guangbo Li, Hewen Li, Yuqi Wang, Wenzhe Wang, Qingyi Liu, and Hongcheng Wang. 2024b · 2024
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Deep Learning for Trajectory Data Management and Mining: A Survey and Beyond
Wei Chen, Yuxuan Liang, Yuanshao Zhu, Yanchuan Chang, Kang Luo, Haomin Wen, Lei Li, Yanwei Yu, Qingsong Wen, Chao Chen, et al · 2024
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RF-Diffusion: Radio Signal Generation via Time-Frequency Diffusion
Guoxuan Chi, Zheng Yang, Chenshu Wu, Jingao Xu, Yuchong Gao, Yunhao Liu, and Tony Xiao Han. 2024 · 2024
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A Gated MLP Architecture for Learning Topological Dependencies in Spatio-Temporal Graphs
Yun Young Choi, Minho Lee, Sun Woo Park, Seunghwan Lee, and Joohwan Ko. 2024 · 2024
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Simulating human mobility with a trajectory generation framework based on diffusion model
Chen Chu, Hengcai Zhang, Peixiao Wang, and Feng Lu. 2024 · 2024
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On the constrained time-series generation problem
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