INNF+ 2020



Accepted Papers


  1. Neural Manifold Ordinary Differential Equations
    Lou, Aaron*; Lim, Derek; Katsman, Isay; Huang, Leo; Jiang, Qingxuan; Lim, Ser-Nam; De Sa, Christopher
    [video]
  2. You say Normalizing Flows I see Bayesian Networks
    Wehenkel, Antoine*; Louppe, Gilles
    [video]
  3. Variational Inference with Continuously-Indexed Normalizing Flows
    Caterini, Anthony L*; Cornish, Rob; Doucet, Arnaud; Sejdinovic, Dino
    [video]
  4. Improving Sample Quality by Training and Sampling from Latent Energy
    Xiao, Zhisheng*; Yan, Qing; Amit, Yali
    [video]
  5. The Convolution Exponential
    Hoogeboom, Emiel*; Garcia Satorras, Víctor; Tomczak, Jakub; Welling, Max
    [video]
  6. Exhaustive Neural Importance Sampling applied to Monte Carlo event generation
    Pina-Otey, Sebastian*; Sanchez, Federico; Lux, Thorsten; Gaitan, Vicens
    [video]
  7. Stochastic Normalizing Flows
    Wu, Hao; Köhler, Jonas; Noe, Frank*
    [video]
  8. Quasi-Autoregressive Residual (QuAR) Flows
    Gopal, Achintya*
    [video]
  9. Time Series Decomposition with Slow Flows
    Pineau, Edouard*; Razakarivony, Sébastien; Bonald, Thomas
    [video]
  10. Faster Orthogonal Parameterization with Householder Matrices
    Mathiasen, Alexander*; Hvilshøj, Frederik; Rødsgaard Jørgensen, Jakob; Nasery, Anshul; Mottin, Davide
    [video]
  11. WaveNODE: A Continuous Normalizing Flow for Speech Synthesis
    Kim, Hyeongju*; Lee, Hyeonseung; Kang, Woo Hyun; Cheon, Sung Jun; Choi, Byoung Jin; Kim, Nam Soo
    [video]
  12. NOTAGAN: Flows for the data manifold
    Brehmer, Johann*; Cranmer, Kyle
    [video]
  13. The Power Spherical distribution
    De Cao, Nicola*; Aziz, Wilker
    [video]
  14. Ordering Dimensions with Nested Dropout Normalizing Flows
    Bekasov, Artur*; Murray, Iain
    [video]
  15. Woodbury Transformations for Deep Generative Flows
    Lu, You*; Huang, Bert
    [video]
  16. Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows
    Deng, Ruizhi*; Chang, Bo; Brubaker, Marcus; Mori, Greg; Lehrmann, Andreas
    [video]
  17. Super-resolution Variational Auto-Encoders
    Gatopoulos, Ioannis*; Stol, Maarten; Tomczak, Jakub M
    [video]
  18. The Lipschitz Constant of Self-Attention
    Kim, Hyunjik*; Papamakarios, George; Mnih, Andriy
    [video]
  19. Conditional Normalizing Flows for Low-Dose Computed Tomography Image Reconstruction
    Denker, Alexander Konstantin*; Schmidt, Maximilian; Leuschner, Johannes; Behrmann, Jens; Maaß, Peter
    [video]
  20. Why Normalizing Flows Fail to Detect Out-of-Distribution Data
    Kirichenko, Polina*; Izmailov, Pavel; Wilson, Andrew Gordon
    [video]
  21. Density Deconvolution with Normalizing Flows
    Dockhorn, Tim*; Ritchie, James A; Yu, Yaoliang; Murray, Iain
    [video]
  22. Consistency Regularization for Variational Auto-encoders
    Sinha, Samrath*; Odena, Augustus; Dieng, Adji Bousso
    [video]
  23. Normalizing Flows with Multi-Scale Autoregressive Priors
    Bhattacharyya, Apratim*; Mahajan, Shweta; Fritz, Mario; Schiele, Bernt; Roth, Stefan
    [video]
  24. Metropolized Flow: from Invertible Flow to MCMC
    Thin, Achille*; Kotelevskii, Nikita; Durmus, Alain; Panov, Maxim; Moulines, Eric
    [video]
  25. Robust model training and generalisation with Studentising flows
    Alexanderson, Simon; Henter, Gustav Eje*
    [video]
  26. Scaling RBMs to High Dimensional Data with Invertible Neural Networks
    Grathwohl, Will*; Li, Xuechen; Swersky, Kevin; Hashemi, Milad; Jacobsen, Joern-Henrik; Norouzi, Mohammad; Hinton, Geoffrey
    [video]
  27. On the Variational Posterior of Dirichlet Process Deep Latent Gaussian Mixture Models
    Echraibi, Amine*
    [video]
  28. Autoregressive flow-based causal discovery and inference
    Monti, Ricardo*; Khemakhem, Ilyes; Hyvarinen, Aapo
    [video]
  29. A Fourier State Space Model for Bayesian ODE Filters
    Kersting, Hans*; Mahsereci, Maren
    [video]
  30. MoFlow: An Invertible Flow Model for Molecular Graph Generation
    Zang, Chengxi*; Wang, Fei
    [video]
  31. Learning normalizing flows from Entropy-Kantorovich potentials
    Finlay, Chris*; Gerolin, Augusto; Oberman, Adam; Pooladian, Aram-Alexandre
    [video]
  32. Neural Ordinary Differential Equations on Manifolds
    Falorsi, Luca*; Forré, Patrick
    [video]
  33. TraDE: Transformers for Density Estimation
    Fakoor, Rasool*; Chaudhari, Pratik; Mueller, Jonas; Smola, Alex J
    [video]
  34. WeakFlow: Iterative Invertible Distribution Transformations via Weak Destructive Flows
    Inouye, David I*; Ravikumar, Pradeep
    [video]
  35. Flow-based SVDD for anomaly detection
    Sendera, Marcin*; Śmieja, Marek; Maziarka, Łukasz; Struski, Łukasz; Spurek, Przemysław; Tabor, Jacek
    [video]
  36. Black-box Adversarial Example Generation with Normalizing Flows
    Mohaghegh Dolatabadi, Hadi*; Erfani, Sarah; Leckie, Christopher
    [video]
  37. Sequential Autoregressive Flow-Based Policies
    Guerra, Alex; Marino, Joe*
    [video]
  38. Relative gradient optimization of the Jacobian term in unsupervised deep learning
    Gresele, Luigi*; Fissore, Giancarlo; Javaloy, Adrian; Schölkopf, Bernhard; Hyvarinen, Aapo
    [video]
  39. Deep Generative Video Compression with Temporal Autoregressive Transforms
    Yang, Ruihan*; Yang, Yibo; Marino, Joe; Yang, Yang; Mandt, Stephan
    [video]
  40. Normalizing Flows Across Dimensions
    Cunningham, Edmond*; Zabounidis, Renos; Agrawal, Abhinav; Fiterau, Madalina; Sheldon, Daniel
    [video]
  41. Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation
    Waites, Christopher*; Cummings, Rachel
    [video]
  42. Model-Agnostic Searches for New Physics with Normalizing Flows
    Tan, Justin *