- Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification
- You say Normalizing Flows I see Bayesian Networks
- Glow: Generative Flow with Invertible 1x1 Convolutions
- Conditional Density Estimation with Bayesian Normalising Flows
- AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows
- FloWaveNet : A Generative Flow for Raw Audio
- Flows for simultaneous manifold learning and density estimation
- ACFlow: Flow Models for Arbitrary Conditional Likelihoods
- Stochastic Normalizing Flows
- Density estimation using Real NVP
- Gradient Boosted Normalizing Flows
- Haar Wavelet based Block Autoregressive Flows for Trajectories
- Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows
- SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows
- Normalizing Flows with Multi-Scale Autoregressive Priors
- Neural Spline Flows
- Normalizing Flows: An Introduction and Review of Current Methods
- A RAD approach to deep mixture models
- Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows
- Invertible Generative Modeling using Linear Rational Splines
- Analyzing Inverse Problems With Invertible Neural Networks
- Integer Discrete Flows and Lossless Compression
- Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities
- Gaussianization Flows
- Sylvester Normalizing Flows for Variational Inference
- Variational Inference with Normalizing Flows
- Normalizing Flows on Tori and Spheres
- Residual Flows for Invertible Generative Modeling
- Block Neural Autoregressive Flow
- Graph Normalizing Flows
- Neural Autoregressive Flows
- Iterative Gaussianization: from ICA to Random Rotations
- FFJORD: Free-form Continuous Dynamics For Scalable Reversible Generative Models
- NICE: Non-linear Independent Components Estimation
- Graphical Normalizing Flows
- Why Normalizing Flows Fail to Detect Out-of-Distribution Data
- Targeted free energy estimation via learned mappings
- Improved Variational Inference with Inverse Autoregressive Flow
- Normalizing Flows for Probabilistic Modeling and Inference
- Multiplicative Normalizing Flows for Variational Bayesian Neural Networks
- Masked Autoregressive Flow for Density Estimation
- NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport
- Unconstrained Monotonic Neural Networks
- Normalizing Kalman Filters for Multivariate Time Series Analysis
- Density Deconvolution with Normalizing Flows
- Deep Density Destructors
- Stochastic Normalizing Flows
- Noise Regularization for Conditional Density Estimation
- MADE: Masked Autoencoder for Distribution Estimation
- On the Sentence Embeddings from Pre-trained Language Models
- SRFlow: Learning the Super-Resolution Space with Normalizing Flow
- SoftFlow: Probabilistic Framework for Normalizing Flow on Manifolds