Generative flows on discrete state-spaces: Enabling multimodal flows with applications to protein co-design
Combining discrete and continuous data is an important capability for generative models.
We present Discrete Flow Models (DFMs), a new flow-based model of discrete data that …
We present Discrete Flow Models (DFMs), a new flow-based model of discrete data that …
How discrete and continuous diffusion meet: Comprehensive analysis of discrete diffusion models via a stochastic integral framework
Discrete diffusion models have gained increasing attention for their ability to model complex
distributions with tractable sampling and inference. However, the error analysis for discrete …
distributions with tractable sampling and inference. However, the error analysis for discrete …
Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms
Discrete diffusion models have emerged as a powerful generative modeling framework for
discrete data with successful applications spanning from text generation to image synthesis …
discrete data with successful applications spanning from text generation to image synthesis …
Lagdif: Latent graph diffusion model for efficient protein inverse folding with self-ensemble
Protein inverse folding aims to identify viable amino acid sequences that can fold into given
protein structures, enabling the design of novel proteins with desired functions for …
protein structures, enabling the design of novel proteins with desired functions for …