ARM-Net is an adaptive relation modeling network tailored for structured data, and a lightweight framework ARMOR based on ARM-Net for relational data analytics. The key idea is to model feature interactions with cross features selectively and dynamically, by first transforming the input features into exponential space, and then determining the interaction order and interaction weights adaptively for each cross feature. The authors propose a novel sparse attention mechanism to dynamically generate the interaction weights given the input tuple, so that we can explicitly model cross features of arbitrary orders with noisy features filtered selectively. Then during model inference, ARM-Net can specify the cross features being used for each prediction for higher accuracy and better interpretability.

**Geomancer** is a nonparametric algorithm for symmetry-based disentangling of data manifolds. It learns a set of subspaces to assign to each point in the dataset, where each subspace is the tangent space of one disentangled submanifold. This means that geomancer can be used to disentangle manifolds for which there may not be a global axis-aligned coordinate system.

GEOMANCER

Disentangling by Subspace Diffusion

ARM-Net

ARM-Net: Adaptive Relation Modeling Network for Structured Data

We propose a deep network architecture for the pansharpening problem called PanNet. We incorporate domain-specific knowledge to design our PanNet architecture by focusing on the two aims of the pan-sharpening problem: spectral and spatial preservation. For spectral preservation, we add up-sampled multispectral images to the network output, which directly propagates the spectral information to the reconstructed image. To preserve the spatial structure, we train our network parameters in the high-pass filtering domain rather than the image domain. We show that the trained network generalizes well to images from different satellites without needing retraining. Experiments show significant improvement over state-of-the-art methods visually and in terms of standard quality metrics.

Source	ARM-Net: Adaptive Relation Modeling Network for Structured Data
Year	2000
Data Source	CC BY-SA - https://paperswithcode.com