arXiv:2005.02819
공식 코드 · Papers with Code
Geoopt: Riemannian Optimization in PyTorch
원문 초록
Geoopt is a research-oriented modular open-source package for Riemannian Optimization in PyTorch. The core of Geoopt is a standard Manifold interface that allows for the generic implementation of optimization algorithms. Geoopt supports basic Riemannian SGD as well as adaptive optimization algorithms. Geoopt also provides several algorithms and arithmetic methods for supported manifolds, which allow composing geometry-aware neural network layers that can be integrated with existing models.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Efficient Optimization with Orthogonality Constraint: a Randomized Riemannian Submanifold Method
Riemannian Optimization on Relaxed Indicator Matrix Manifold
Causal Abstraction Learning based on the Semantic Embedding Principle
A Spectral Framework for Tracking Communities in Evolving Networks
Elliptical Wishart distributions: information geometry, maximum likelihood estimator, performance analysis and statistical learning
The Gaussian Discriminant Variational Autoencoder (GdVAE): A Self-Explainable Model with Counterfactual Explanations
토론
이 논문과 연결된 포럼 글이 아직 없습니다.