activity
20182022
most citedStability and Generalization of Graph Convolutional Neural Networks

12 citations · 14 across the 4 of their papers we have counts for

collaborators

7 papers

cs.AI20201 cited

TIES: Temporal Interaction Embeddings For Enhancing Social Media Integrity At Facebook

Nima Noorshams, Saurabh Verma, Aude Hofleitner

Since its inception, Facebook has become an integral part of the online social community. People rely on Facebook to make connections with others and build communities. As a result…

cs.LG2020

Physics-Guided Deep Neural Networks for Power Flow Analysis

Xinyue Hu, Haoji Hu, Saurabh Verma +1

Solving power flow (PF) equations is the basis of power flow analysis, which is important in determining the best operation of existing systems, performing security analysis, etc.…

cs.LG2019

Learning Universal Graph Neural Network Embeddings With Aid Of Transfer Learning

Saurabh Verma, Zhi-Li Zhang

Learning powerful data embeddings has become a center piece in machine learning, especially in natural language processing and computer vision domains. The crux of these embeddings…

cs.LG2019

A Fast-Optimal Guaranteed Algorithm For Learning Sub-Interval Relationships in Time Series

Saurabh Agrawal, Saurabh Verma, Anuj Karpatne +3

Traditional approaches focus on finding relationships between two entire time series, however, many interesting relationships exist in small sub-intervals of time and remain feeble…

cs.LG201912 cited

Stability and Generalization of Graph Convolutional Neural Networks

Saurabh Verma, Zhi-Li Zhang

Inspired by convolutional neural networks on 1D and 2D data, graph convolutional neural networks (GCNNs) have been developed for various learning tasks on graph data, and have show…

stat.ML2018

Graph Capsule Convolutional Neural Networks

Saurabh Verma, Zhi-Li Zhang

Graph Convolutional Neural Networks (GCNNs) are the most recent exciting advancement in deep learning field and their applications are quickly spreading in multi-cross-domains incl…