Patrick Emami

Learning Permutations with Sinkhorn Policy Gradient

2018 · arXiv (Cornell University)

Many problems at the intersection of combinatorics and computer science require solving for a permutation that optimally matches, ranks, or sorts some data. These problems usually have a task-specific, often non-differentiable objective function that data-driven …

Toward Improving the Generation Quality of Autoregressive Slot VAEs

2024 · Neural Computation

Unconditional scene inference and generation are challenging to learn jointly with a single compositional model. Despite encouraging progress on models that extract object-centric representations ("slots") from images, unconditional generation of scenes from slots has received …