Evolutionary One-Step Generators: Fast and Diverse Sampling for Discrete Design
cs.LG, cs.NE
Submitted: 2026-10-06
Updated: 2026-10-06
Sources
- Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
- MolGAN: An implicit generative model for small molecular graphs
- Generative Modeling via Drifting
- Kernel-Gradient Drifting Models
- PairFlow: Closed-Form Source-Target Coupling for Few-Step Generation in Discrete Flow Models
- Categorical Flow Maps
- Evolution Strategies as a Scalable Alternative to Reinforcement Learning
- Evolution Strategies at the Hyperscale
- Learning Flexible Forward Trajectories for Masked Molecular Diffusion
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