Home /
Research
Showing 55 - 60 / 904
Algebraically-Informed Deep Networks (AIDN): A Deep Learning Approach to Represent Algebraic Structures
MustafaHajij, GhadaZamzmi, MatthewDawson....
Published date-12/02/2020
One of the central problems in the interface of deep learning and mathematics is that of building learning systems that can automatically uncover underlying mathematical laws from observed data. In …
PlueckerNet: Learn to Register 3D Line Reconstructions
LiuLiu, HongdongLi, HaodongYao....
Published date-12/02/2020
Aligning two partially-overlapped 3D line reconstructions in Euclidean space is challenging, as we need to simultaneously solve correspondences and relative pose between line reconstructions. This paper proposes a neural network …
Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples
JayNandy, WynneHsu, MongLiLee....
Published date-12/01/2020
Among existing uncertainty estimation approaches, Dirichlet Prior Network (DPN) distinctly models different predictive uncertainty types. However, for in-domain examples with high data uncertainties among multiple classes, even a DPN model …
Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks
HongweiJin, ZhanShi, VenkataJayaShankarAshishPeruri....
Published date-12/01/2020
GraphClassification
Graph convolution networks (GCNs) have become effective models for graph classification. Similar to many deep networks, GCNs are vulnerable to adversarial attacks on graph topology and node attributes. Recently, a …
Graph Stochastic Neural Networks for Semi-supervised Learning
HaiboWang, ChuanZhou, XinChen....
Published date-12/01/2020
NodeClassification, VariationalInference
Graph Neural Networks (GNNs) have achieved remarkable performance in the task of the semi-supervised node classification. However, most existing models learn a deterministic classification function, which lack sufficient flexibility to …
Grabber: A tool to improve convergence in interactive image segmentation
JordãoBragantini, BrunoMoura, AlexandreXavierFalcão....
Published date-12/01/2020
SemanticSegmentation
Interactive image segmentation has considerably evolved from techniques that do not learn the parameters of the model to methods that pre-train a model and adapt it from user inputs during …