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graph construction

18 papers with code · Graphs

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DyNet: The Dynamic Neural Network Toolkit

15 Jan 2017clab/cnn

In the static declaration strategy that is used in toolkits like Theano, CNTK, and TensorFlow, the user first defines a computation graph (a symbolic representation of the computation), and then examples are fed into an engine that executes this computation and computes its derivatives.

GRAPH CONSTRUCTION

Visualizing Large-scale and High-dimensional Data

1 Feb 2016lferry007/LargeVis

We propose the LargeVis, a technique that first constructs an accurately approximated K-nearest neighbor graph from the data and then layouts the graph in the low-dimensional space.

GRAPH CONSTRUCTION

EFANNA : An Extremely Fast Approximate Nearest Neighbor Search Algorithm Based on kNN Graph

23 Sep 2016ZJULearning/nsg

In this paper, we propose EFANNA, an extremely fast approximate nearest neighbor search algorithm based on $k$NN Graph.

GRAPH CONSTRUCTION

COMET: Commonsense Transformers for Automatic Knowledge Graph Construction

ACL 2019 atcbosselut/comet-commonsense

We present the first comprehensive study on automatic knowledge base construction for two prevalent commonsense knowledge graphs: ATOMIC (Sap et al., 2019) and ConceptNet (Speer et al., 2017).

GRAPH CONSTRUCTION KNOWLEDGE GRAPHS

LEARNING TO PROPAGATE LABELS: TRANSDUCTIVE PROPAGATION NETWORK FOR FEW-SHOT LEARNING

ICLR 2019 csyanbin/TPN

The goal of few-shot learning is to learn a classifier that generalizes well even when trained with a limited number of training instances per class.

FEW-SHOT LEARNING GRAPH CONSTRUCTION META-LEARNING

Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition

CVPR 2019 lshiwjx/2s-AGCN

In addition, the second-order information (the lengths and directions of bones) of the skeleton data, which is naturally more informative and discriminative for action recognition, is rarely investigated in existing methods.

GRAPH CONSTRUCTION SKELETON BASED ACTION RECOGNITION

Towards Dynamic Computation Graphs via Sparse Latent Structure

EMNLP 2018 vene/sparsemap

Deep NLP models benefit from underlying structures in the data---e. g., parse trees---typically extracted using off-the-shelf parsers.

GRAPH CONSTRUCTION

IPRE: a Dataset for Inter-Personal Relationship Extraction

30 Jul 2019SUDA-HLT/IPRE

Our data is the first dataset for inter-personal relationship extraction.

GRAPH CONSTRUCTION

Low-shot learning with large-scale diffusion

CVPR 2018 facebookresearch/low-shot-with-diffusion

This paper considers the problem of inferring image labels from images when only a few annotated examples are available at training time.

GRAPH CONSTRUCTION

IPC: A Benchmark Data Set for Learning with Graph-Structured Data

15 May 2019IBM/IPC-graph-data

Benchmark data sets are an indispensable ingredient of the evaluation of graph-based machine learning methods.

BENCHMARKING GRAPH CLASSIFICATION GRAPH CONSTRUCTION