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43 lines (43 loc) · 1.21 KB
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cff-version: 1.2.0
message: "If you use this software, please cite it as below."
type: software
title: "polystep: Gradient-Free Neural Network Training via Optimal Transport"
authors:
- family-names: Le
given-names: An T.
license: Apache-2.0
version: 0.13.0
date-released: "2026-09-22"
repository-code: "https://github.com/anindex/polystep"
keywords:
- gradient-free optimization
- optimal transport
- sinkhorn
- pytorch
- neural network training
- non-differentiable
preferred-citation:
type: article
title: "Training Non-Differentiable Networks via Optimal Transport"
authors:
- family-names: Le
given-names: An T.
journal: "arXiv preprint arXiv:2605.01928"
year: 2026
url: "https://arxiv.org/abs/2605.01928"
references:
- type: conference-paper
title: "Accelerating Motion Planning via Optimal Transport"
authors:
- family-names: Le
given-names: An T.
- family-names: Chalvatzaki
given-names: Georgia
- family-names: Biess
given-names: Armin
- family-names: Peters
given-names: Jan R.
conference:
name: "Advances in Neural Information Processing Systems (NeurIPS)"
year: 2023
url: "https://arxiv.org/abs/2309.15970"