arXiv:2404.10761
공식 코드 · Papers with Code
TorchSurv: A Lightweight Package for Deep Survival Analysis
원문 초록
TorchSurv is a Python package that serves as a companion tool to perform deep survival modeling within the PyTorch environment. Unlike existing libraries that impose specific parametric forms, TorchSurv enables the use of custom PyTorch-based deep survival models. With its lightweight design, minimal input requirements, full PyTorch backend, and freedom from restrictive survival model parameterizations, TorchSurv facilitates efficient deep survival model implementation and is particularly beneficial for high-dimensional and complex input data scenarios.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Survival Analysis as Imprecise Classification with Trainable Kernels
SurvUnc: A Meta-Model Based Uncertainty Quantification Framework for Survival Analysis
Multimodal Cancer Survival Analysis via Hypergraph Learning with Cross-Modality Rebalance
Multi-Resolution Pathology-Language Pre-training Model with Text-Guided Visual Representation
Beyond Cox Models: Assessing the Performance of Machine-Learning Methods in Non-Proportional Hazards and Non-Linear Survival Analysis
Offline Dynamic Inventory and Pricing Strategy: Addressing Censored and Dependent Demand
토론
이 논문과 연결된 포럼 글이 아직 없습니다.