论文标题
胶囊网络 - 概率的观点
Capsule Networks -- A Probabilistic Perspective
论文作者
论文摘要
“胶囊”模型试图明确表示对象的姿势，从而在对象的姿势与其组成部分的姿势之间存在线性关系。这种建模假设应导致对观点变化的鲁棒性，因为子对象/超对象的关系是对象姿势的不变性。我们描述了一个概率的生成模型，该模型编码了此类胶囊假设，清楚地将模型的生成部分与推理机理分开。通过变异结合，我们独立于近似推理方案探索生成模型的特性，并获得对胶囊假设和推理摊销失败的见解。我们在实验上证明了我们统一目标的适用性，并证明了测试时间优化的使用来解决模型中摊销推断固有的问题。
'Capsule' models try to explicitly represent the poses of objects, enforcing a linear relationship between an object's pose and that of its constituent parts. This modelling assumption should lead to robustness to viewpoint changes since the sub-object/super-object relationships are invariant to the poses of the object. We describe a probabilistic generative model which encodes such capsule assumptions, clearly separating the generative parts of the model from the inference mechanisms. With a variational bound we explore the properties of the generative model independently of the approximate inference scheme, and gain insights into failures of the capsule assumptions and inference amortisation. We experimentally demonstrate the applicability of our unified objective, and demonstrate the use of test time optimisation to solve problems inherent to amortised inference in our model.
