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08/04/2023
VQGraph: Graph Vector-Quantization for Bridging GNNs and MLPs
Graph Neural Networks (GNNs) conduct message passing which aggregates lo...
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01/28/2023
Zero-shot causal learning
Predicting how different interventions will causally affect a specific i...
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11/22/2022
Retrieval-Augmented Multimodal Language Modeling
Recent multimodal models such as DALL-E and CM3 have achieved remarkable...
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06/15/2022
Learning Large-scale Subsurface Simulations with a Hybrid Graph Network Simulator
Subsurface simulations use computational models to predict the flow of f...
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05/23/2022
VQA-GNN: Reasoning with Multimodal Semantic Graph for Visual Question Answering
Visual understanding requires seamless integration between recognition a...
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05/21/2022
MultiBiSage: A Web-Scale Recommendation System Using Multiple Bipartite Graphs at Pinterest
Graph Convolutional Networks (GCN) can efficiently integrate graph struc...
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04/13/2021
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
The problem of answering questions using knowledge from pre-trained lang...
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02/10/2021
Driver2vec: Driver Identification from Automotive Data
With increasing focus on privacy protection, alternative methods to iden...
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12/14/2020
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Distribution shifts can cause significant degradation in a broad range o...
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07/07/2020
PinnerSage: Multi-Modal User Embedding Framework for Recommendations at Pinterest
Latent user representations are widely adopted in the tech industry for ...
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05/02/2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs
We present the Open Graph Benchmark (OGB), a diverse set of challenging ...
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02/17/2020
Entity Context and Relational Paths for Knowledge Graph Completion
Knowledge graph completion aims to predict missing relations between ent...
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10/28/2019
Hyperbolic Graph Convolutional Neural Networks
Graph convolutional neural networks (GCNs) embed nodes in a graph into E...
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06/26/2019
Selection Via Proxy: Efficient Data Selection For Deep Learning
Data selection methods such as active learning and core-set selection ar...
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05/11/2019
Knowledge Graph Convolutional Networks for Recommender Systems with Label Smoothness Regularization
Knowledge graphs capture interlinked information between entities and th...
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03/10/2019
GNN Explainer: A Tool for Post-hoc Explanation of Graph Neural Networks
Graph Neural Networks (GNNs) are a powerful tool for machine learning on...
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12/05/2018
Predicting pregnancy using large-scale data from a women's health tracking mobile application
Predicting pregnancy has been a fundamental problem in women's health fo...
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09/06/2018
CASC: Context-Aware Segmentation and Clustering for Motif Discovery in Noisy Time Series Data
Complex systems, such as airplanes, cars, or financial markets, produce ...
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06/05/2018
Querying Complex Networks in Vector Space
Learning vector embeddings of complex networks is a powerful approach us...
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05/07/2018
Prioritizing network communities
Uncovering modular structure in networks is fundamental for advancing th...
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11/21/2017
Pixie: A System for Recommending 3+ Billion Items to 200+ Million Users in Real-Time
User experience in modern content discovery applications critically depe...
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06/09/2016
