flow-based generative model
A type of generative model that uses invertible transformations to generate data, allowing exact likelihood computation and enabling efficient sampling.
- A solvable model of learning generative diffusion: theory and insights
- HollowFlow: Efficient Sample Likelihood Evaluation using Hollow Message Passing
- Modeling Microenvironment Trajectories on Spatial Transcriptomics with NicheFlow
- NeuralPLexer3: Accurate Biomolecular Complex Structure Prediction with Flow Models
- PhySense: Sensor Placement Optimization for Accurate Physics Sensing
- PhySense: Sensor Placement Optimization for Accurate Physics Sensing