arXiv:1707.03003
공식 코드 · Papers with Code
Tick: a Python library for statistical learning, with a particular emphasis on time-dependent modelling
원문 초록
Tick is a statistical learning library for Python~3, with a particular emphasis on time-dependent models, such as point processes, and tools for generalized linear models and survival analysis. The core of the library is an optimization module providing model computational classes, solvers and proximal operators for regularization. tick relies on a C++ implementation and state-of-the-art optimization algorithms to provide very fast computations in a single node multi-core setting. Source code and documentation can be downloaded from https://github.com/X-DataInitiative/tick
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MS-DPPs: Multi-Source Determinantal Point Processes for Contextual Diversity Refinement of Composite Attributes in Text to Image Retrieval
Towards Reliable Detection of Empty Space: Conditional Marked Point Processes for Object Detection
Survival Analysis as Imprecise Classification with Trainable Kernels
SurvUnc: A Meta-Model Based Uncertainty Quantification Framework for Survival Analysis
Turbocharging Gaussian Process Inference with Approximate Sketch-and-Project
Multimodal Cancer Survival Analysis via Hypergraph Learning with Cross-Modality Rebalance
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