1. Neural Diffusion Processes
    Vincent Dutordoir, Alan Saul, Zoubin Ghahramani, Fergus Simpson
    arXiv 2022. Paper  
    2022-06-08
    2022-06-08
  2. Diffusion probabilistic modeling of protein backbones in 3D for the motif-scaffolding problem*
    Brian L. Trippe1, Jason Yim1, Doug Tischer, Tamara Broderick, David Baker, Regina Barzilay, Tommi Jaakkola
    arXiv 2022. Paper  
    2022-06-08
    2022-06-08
  3. Theory and Algorithms for Diffusion Processes on Riemannian Manifolds
    Bowen Jing, Gabriele Corso, Jeffrey Chang, Regina Barzilay, Tommi Jaakkola
    arXiv 2022. Paper   Github  
    2022-06-01
    2022-06-01
  4. Guided Diffusion Model for Adversarial Purification
    Jinyi Wang1, Zhaoyang Lyu1, Dahua Lin, Bo Dai, Hongfei Fu
    arXiv 2022. Paper  
    2022-05-30
    2022-05-30
  5. Diffusion-LM Improves Controllable Text Generation
    Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B. Hashimoto
    arXiv 2022. Paper  
    2022-05-27
    2022-05-27
  6. Protein Structure and Sequence Generation with Equivariant Denoising Diffusion Probabilistic Models
    Namrata Anand, Tudor Achim
    arXiv 2022. Paper   Project  
    2022-05-26
    2022-05-26
  7. Planning with Diffusion for Flexible Behavior Synthesis
    Michael Janner, Yilun Du, Joshua B. Tenenbaum, Sergey Levine
    arxiv 2022. Paper  
    2022-05-20
    2022-05-20
  8. Diffusion Models for Adversarial Purification
    Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar
    ICML 2022. Paper   Project  
    2022-05-16
    2022-05-16
  9. Bayesian Learning via Stochastic Gradient Langevin Dynamics
    Max Welling, Yee Whye Teh
    ICML 2011. Paper   Github  
    2022-04-20
    2022-04-20
  10. A Score-based Geometric Model for Molecular Dynamics Simulations
    Fang Wu1, Qiang Zhang1, Xurui Jin, Yinghui Jiang, Stan Z. Li
    arXiv 2022. Paper  
    2022-04-19
    2022-04-19
  11. Equivariant Diffusion for Molecule Generation in 3D
    Emiel Hoogeboom1, Victor Garcia Satorras1, Clément Vignac, Max Welling
    arXiv 2022. Paper  
    2022-03-31
    2022-03-31
  12. Stochastic Trajectory Prediction via Motion Indeterminacy Diffusion
    Tianpei Gu1, Guangyi Chen1, Junlong Li, Chunze Lin, Yongming Rao, Jie Zhou, Jiwen L
    arXiv 2022. Paper  
    2022-03-25
    2022-03-25
  13. GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation
    Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, Jian Tang
    ICLR 2022. Paper  
    2022-03-06
    2022-03-06
  14. Riemannian Score-Based Generative Modeling
    Valentin De Bortoli1, Emile Mathieu1, Michael Hutchinson, James Thornton, Yee Whye Teh, Arnaud Doucet
    arXiv 2022. Paper  
    2022-02-06
    2022-02-06
  15. TFDPM: Attack detection for cyber-physical systems with diffusion probabilistic models
    Tijin Yan, Tong Zhou, Yufeng Zhan, Yuanqing Xia
    arXiv 2021. Paper  
    2021-12-20
    2021-12-20
  16. Deep Diffusion Models for Robust Channel Estimation
    Marius Arvinte, Jonathan I Tamir
    arXiv 2021. Paper   Github  
    2021-11-16
    2021-11-16
  17. Deep diffusion-based forecasting of COVID-19 by incorporating network-level mobility information
    Padmaksha Roy, Shailik Sarkar, Subhodip Biswas, Fanglan Chen, Zhiqian Chen, Naren Ramakrishnan, Chang-Tien Lu
    arXiv 2021. Paper  
    2021-11-09
    2021-11-09
  18. Realistic galaxy image simulation via score-based generative models
    Michael J. Smith (Hertfordshire), James E. Geach, Ryan A. Jackson, Nikhil Arora, Connor Stone, Stéphane Courteau
    MNRAS 2022. Paper  
    2021-11-02
    2021-11-02
  19. Zero-Shot Translation using Diffusion Models
    Eliya Nachmani1, Shaked Dovrat1
    arXiv 2021. Paper  
    2021-11-02
    2021-11-02
  20. Crystal Diffusion Variational Autoencoder for Periodic Material Generation
    Tian Xie1, Xiang Fu1, Octavian-Eugen Ganea1, Regina Barzilay, Tommi Jaakkol
    arXiv 2021. Paper  
    2021-10-12
    2021-10-12
  21. CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation
    Yusuke Tashiro, Jiaming Song, Yang Song, Stefano Ermon
    NeurIPS 2021. Paper   Github  
    2021-07-07
    2021-07-07
  22. ScoreGrad: Multivariate Probabilistic Time Series Forecasting with Continuous Energy-based Generative Models
    Tijin Yan, Hongwei Zhang, Tong Zhou, Yufeng Zhan, Yuanqing Xia
    arXiv 2021. Paper   Github  
    2021-06-18
    2021-06-18
  23. Adversarial purification with Score-based generative models
    Jongmin Yoon, Sung Ju Hwang, Juho Lee
    ICML 2021. Paper   Github  
    2021-06-11
    2021-06-11
  24. Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting
    Kashif Rasul, Calvin Seward, Ingmar Schuster, Roland Vollgraf
    ICLR 2021. Paper   Github  
    2021-02-02
    2021-02-02
  25. Diffusion models for Handwriting Generation
    Troy Luhman1, Eric Luhman1
    arXiv 2020. Paper   Github  
    2020-11-13
    2020-11-13
  26. Permutation Invariant Graph Generation via Score-Based Generative Modeling
    Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, Stefano Ermon
    AISTATS 2021. Paper   Github  
    2020-03-02
    2020-03-02
  27. A Connection Between Score Matching and Denoising Autoencoders
    Pascal Vincent
    Neural Computation 2011. Paper  
    2011-07-07
    2011-07-07
Counts - 27   Back to top