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Found 18 papers, 2 papers with code
Keyword Augmentation via Generative Methods
In this paper, we propose a keyword augmentation method based on generative seq2seq model and trie-based search mechanism, which is able to generate high-quality keywords for any products or product lists.
Dynamic Gaussian Graph Operator: Learning parametric partial differential equations in arbitrary discrete mechanics problems
Metric vectors are regarded as located on latent uniform domain, wherein spatial and spectral transformation offer highly regular constraints on solution space.
MPIPN: A Multi Physics-Informed PointNet for solving parametric acoustic-structure systems
The framework is generalized to deal with new parametric conditions of systems.
IH-ViT: Vision Transformer-based Integrated Circuit Appear-ance Defect Detection
For the problems of low recognition rate and slow recognition speed of traditional detection methods in IC appearance defect detection, we propose an IC appearance defect detection algo-rithm IH-ViT.
Data-driven prognostics based on time-frequency analysis and symbolic recurrent neural network for fuel cells under dynamic load
Data-centric prognostics is beneficial to improve the reliability and safety of proton exchange membrane fuel cell (PEMFC).
ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction
Natural reading orders of words are crucial for information extraction from form-like documents.
Affinity Graph Supervision for Visual Recognition
Affinity graphs are widely used in deep architectures, including graph convolutional neural networks and attention networks.
Dominant Set Clustering and Pooling for Multi-View 3D Object Recognition
We improve upon these methods by introducing a view clustering and pooling layer based on dominant sets.
FAN: Focused Attention Networks
Thus far the learning of attention weights has been driven solely by the minimization of task specific loss functions.
ProductNet: a Collection of High-Quality Datasets for Product Representation Learning
ProductNet is a collection of high-quality product datasets for better product understanding.
Reference Product Search
For a product of interest, we propose a search method to surface a set of reference products.
Anomaly Detection via Minimum Likelihood Generative Adversarial Networks
Anomaly detection aims to detect abnormal events by a model of normality.
Local Spectral Graph Convolution for Point Set Feature Learning
In the present article, we propose to overcome this limitation by using spectral graph convolution on a local graph, combined with a novel graph pooling strategy.
Ranked #83 on
3D Point Cloud Classification
on ModelNet40
Optimal Learning for Sequential Decision Making for Expensive Cost Functions with Stochastic Binary Feedbacks
We also show that the knowledge gradient policy is asymptotically optimal in an offline setting.
A New Family of Near-metrics for Universal Similarity
We show that for structured data including categorical and continuous data, the near-metrics corresponding to normalized forward k-step diffusion (k small) work as one of the best performing similarity measures; for vector representations of text and images including those extracted from deep learning, the near-metrics derived from normalized and reverse k-step graph diffusion (k very small) exhibit outstanding ability to distinguish data points from different classes.
Self-Sustaining Iterated Learning
An important result from psycholinguistics (Griffiths & Kalish, 2005) states that no language can be learned iteratively by rational agents in a self-sustaining manner.
Functional Frank-Wolfe Boosting for General Loss Functions
Yet, as the number of base hypotheses becomes larger, boosting can lead to a deterioration of test performance.
The Knowledge Gradient with Logistic Belief Models for Binary Classification
We consider sequential decision making problems for binary classification scenario in which the learner takes an active role in repeatedly selecting samples from the action pool and receives the binary label of the selected alternatives.
