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09/30/2022
Graph Neural Networks for Link Prediction with Subgraph Sketching
Many Graph Neural Networks (GNNs) perform poorly compared to simple heur...
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02/09/2022
Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs
Cellular sheaves equip graphs with "geometrical" structure by assigning ...
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11/29/2021
Understanding over-squashing and bottlenecks on graphs via curvature
Most graph neural networks (GNNs) use the message passing paradigm, in w...
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11/23/2021
On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features
While Graph Neural Networks (GNNs) have recently become the de facto sta...
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10/18/2021
Beltrami Flow and Neural Diffusion on Graphs
We propose a novel class of graph neural networks based on the discretis...
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06/21/2021
GRAND: Graph Neural Diffusion
We present Graph Neural Diffusion (GRAND) that approaches deep learning ...
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09/08/2019
What is the value of experimentation measurement?
Experimentation and Measurement (E M) capabilities allow organizations...
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02/22/2019
Scalable Hyperbolic Recommender Systems
We present a large scale hyperbolic recommender system. We discuss why h...
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07/11/2018
A Recurrent Neural Network Survival Model: Predicting Web User Return Time
The size of a website's active user base directly affects its value. Thu...
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06/07/2018
Designing Experiments to Measure Incrementality on Facebook
The importance of Facebook advertising has risen dramatically in recent ...
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04/11/2018
Predicting Twitter User Socioeconomic Attributes with Network and Language Information
Inferring socioeconomic attributes of social media users such as occupat...
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03/16/2018
Online Controlled Experiments for Personalised e-Commerce Strategies: Design, Challenges, and Pitfalls
Online controlled experiments are the primary tool for measuring the cau...
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12/04/2017
Speeding Up BigClam Implementation on SNAP
We perform a detailed analysis of the C++ implementation of the Cluster ...
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06/29/2017
Generalising Random Forest Parameter Optimisation to Include Stability and Cost
Random forests are among the most popular classification and regression ...
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05/29/2017
Neural Embeddings of Graphs in Hyperbolic Space
Neural embeddings have been used with great success in Natural Language ...
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03/07/2017
Customer Lifetime Value Prediction Using Embeddings
We describe the Customer LifeTime Value (CLTV) prediction system deploye...
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01/18/2016
Probabilistic Inference of Twitter Users' Age based on What They Follow
Twitter provides an open and rich source of data for studying human beha...
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01/15/2016
