Fetching the paper…
Reading the bibliography…
Machine learning tasks involving biomedical signals frequently grapple with issues such as limited data availability, imbalanced datasets, labeling complexities, and the interference of measurement noise.
Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals
Ary L Goldberger, Luis AN Amaral, Leon Glass, Jeffrey M Hausdorff, Plamen Ch Ivanov, Roger G Mark, Joseph E Mietus, George B Moody, Chung-Kang Peng, and H Eugene Stanley · 2000
Earlier work this paper cites.
The impact of the mit-bih arrhythmia database
George B Moody and Roger G Mark · 2001
Earlier work this paper cites.
Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
Earlier work this paper cites.
C-rnn-gan: Continuous recurrent neural networks with adversarial training
Olof Mogren · 2016
Earlier work this paper cites.
Wavenet: A generative model for raw audio
Aaron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior, and Koray Kavukcuoglu · 2016
Earlier work this paper cites.
Human activity recognition with smartphone sensors using deep learning neural networks
Charissa Ann Ronao and Sung-Bae Cho · 2016
Earlier work this paper cites.
Real-valued (medical) time series generation with recurrent conditional gans
Cristóbal Esteban, Stephanie L Hyland, and Gunnar Rätsch · 2017
Earlier work this paper cites.
Unimib shar: A dataset for human activity recognition using acceleration data from smartphones
Daniela Micucci, Marco Mobilio, and Paolo Napoletano · 2017
Earlier work this paper cites.
Ecg heartbeat classification: A deep transferable representation
Mohammad Kachuee, Shayan Fazeli, and Majid Sarrafzadeh · 2018
Earlier work this paper cites.
Umap: Uniform manifold approximation and projection for dimension reduction
Leland McInnes, John Healy, and James Melville · 2018
Earlier work this paper cites.
Multivariate time series imputation with variational autoencoders
Vincent Fortuin, Gunnar Rätsch, and Stephan Mandt · 2019
Cited alongside, same era.
Deep learning-based electroencephalography analysis: a systematic review
Yannick Roy, Hubert Banville, Isabela Albuquerque, Alexandre Gramfort, Tiago H Falk, and Jocelyn Faubert · 2019
Cited alongside, same era.
Time-series generative adversarial networks
Jinsung Yoon, Daniel Jarrett, and Mihaela Van der Schaar · 2019
Cited alongside, same era.
Data augmentation for time series: Traditional vs generative models on capacitive proximity time series
Biying Fu, Florian Kirchbuchner, and Arjan Kuijper · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models, 2021
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
Later among the works it cites.
Csdi: Conditional score-based diffusion models for probabilistic time series imputation
Yusuke Tashiro, Jiaming Song, Yang Song, and Stefano Ermon · 2021
Later among the works it cites.
Diffusion models in ai – everything you need to know, 2021
Unite.AI · 2021
Later among the works it cites.
Diffusion-based time series imputation and forecasting with structured state space models
Juan Miguel Lopez Alcaraz and Nils Strodthoff · 2022
Later among the works it cites.
Tts-gan: A transformer-based time-series generative adversarial network
Xiaomin Li, Vangelis Metsis, Huangyingrui Wang, and Anne Hee Hiong Ngu · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Zhifeng Kong, Wei Ping, Jiaji Huang, Kexin Zhao, and Bryan Catanzaro · 2020
Cited alongside, same era.
Conditional sig-wasserstein gans for time series generation
Hao Ni, Lukasz Szpruch, Magnus Wiese, Shujian Liao, and Baoren Xiao · 2020
Cited alongside, same era.
Improved techniques for training score-based generative models
Yang Song and Stefano Ermon · 2020
Cited alongside, same era.
An introduction to variational inference
Ankush Ganguly and Samuel WF Earp · 2021
Cited alongside, same era.
Xiaomin Li, Anne Hee Hiong Ngu, and Vangelis Metsis · 2022
Later among the works it cites.
Image super-resolution via iterative refinement
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J Fleet, and Mohammad Norouzi · 2022
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 · 2022
Later among the works it cites.
Diffusion generative models in infinite dimensions
Olivier Garnier, Grant M. Rotskoff, and Eric Vanden-Eijnden · 2023
Later among the works it cites.