b'Jure Leskovec'

research

∙ 08/06/2023

Communication-Free Distributed GNN Training with Vertex Cut

Training Graph Neural Networks (GNNs) on real-world graphs consisting of...

0 Kaidi Cao, et al. ∙

research

∙ 08/04/2023

VQGraph: Graph Vector-Quantization for Bridging GNNs and MLPs

Graph Neural Networks (GNNs) conduct message passing which aggregates lo...

0 Ling Yang, et al. ∙

research

∙ 07/27/2023

Med-Flamingo: a Multimodal Medical Few-shot Learner

Medicine, by its nature, is a multifaceted domain that requires the synt...

0 Michael Moor, et al. ∙

research

∙ 07/03/2023

Temporal Graph Benchmark for Machine Learning on Temporal Graphs

We present the Temporal Graph Benchmark (TGB), a collection of challengi...

0 Shenyang Huang, et al. ∙

research

∙ 06/07/2023

Enabling tabular deep learning when d ≫ n with an auxiliary knowledge graph

Machine learning models exhibit strong performance on datasets with abun...

0 Camilo Ruiz, et al. ∙

research

∙ 05/23/2023

Uncertainty Quantification over Graph with Conformalized Graph Neural Networks

Graph Neural Networks (GNNs) are powerful machine learning prediction mo...

0 Kexin Huang, et al. ∙

research

∙ 05/21/2023

PRODIGY: Enabling In-context Learning Over Graphs

In-context learning is the ability of a pretrained model to adapt to nov...

0 Qian Huang, et al. ∙

research

∙ 05/02/2023

Geometric Latent Diffusion Models for 3D Molecule Generation

Generative models, especially diffusion models (DMs), have achieved prom...

0 Minkai Xu, et al. ∙

research

∙ 05/01/2023

Learning Controllable Adaptive Simulation for Multi-resolution Physics

Simulating the time evolution of physical systems is pivotal in many sci...

0 Tailin Wu, et al. ∙

research

∙ 04/25/2023

When Do Graph Neural Networks Help with Node Classification: Investigating the Homophily Principle on Node Distinguishability

Homophily principle, i.e. nodes with the same labels are more likely to ...

27 Sitao Luan, et al. ∙

research

∙ 03/26/2023

Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databases

Complex logical query answering (CLQA) is a recently emerged task of gra...

0 Hongyu Ren, et al. ∙

research

∙ 03/14/2023

AutoTransfer: AutoML with Knowledge Transfer – An Application to Graph Neural Networks

AutoML has demonstrated remarkable success in finding an effective neura...

6 Kaidi Cao, et al. ∙

research

∙ 03/14/2023

Relational Multi-Task Learning: Modeling Relations between Data and Tasks

A key assumption in multi-task learning is that at the inference time th...

2 Kaidi Cao, et al. ∙

research

∙ 02/04/2023

Harnessing Simulation for Molecular Embeddings

While deep learning has unlocked advances in computational biology once ...

0 Christopher Fifty, et al. ∙

research

∙ 01/28/2023

Zero-shot causal learning

Predicting how different interventions will causally affect a specific i...

10 Hamed Nilforoshan, et al. ∙

research

∙ 12/12/2022

Estimating Geographic Spillover Effects of COVID-19 Policies From Large-Scale Mobility Networks

Many policies in the US are determined locally, e.g., at the county-leve...

0 Serina Chang, et al. ∙

research

∙ 12/07/2022

Learning Graph Search Heuristics

Searching for a path between two nodes in a graph is one of the most wel...

0 Michal Pándy, et al. ∙

research

∙ 11/22/2022

Retrieval-Augmented Multimodal Language Modeling

Recent multimodal models such as DALL-E and CM3 have achieved remarkable...

28 Michihiro Yasunaga, et al. ∙

research

∙ 10/31/2022

CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation Data

Mapping biological mechanisms in cellular systems is a fundamental step ...

0 Mathieu Chevalley, et al. ∙

research

∙ 10/26/2022

TuneUp: A Training Strategy for Improving Generalization of Graph Neural Networks

Despite many advances in Graph Neural Networks (GNNs), their training st...

0 Weihua Hu, et al. ∙

research

∙ 10/21/2022

Efficient Automatic Machine Learning via Design Graphs

Despite the success of automated machine learning (AutoML), which aims t...

1 Shirley Wu, et al. ∙

research

∙ 10/17/2022

Deep Bidirectional Language-Knowledge Graph Pretraining

Pretraining a language model (LM) on text has been shown to help various...

4 Michihiro Yasunaga, et al. ∙

research

∙ 10/13/2022

Few-shot Relational Reasoning via Connection Subgraph Pretraining

Few-shot knowledge graph (KG) completion task aims to perform inductive ...

10 Qian Huang, et al. ∙

research

∙ 08/15/2022

ROLAND: Graph Learning Framework for Dynamic Graphs

Graph Neural Networks (GNNs) have been successfully applied to many real...

6 Jiaxuan You, et al. ∙

research

∙ 07/04/2022

ViRel: Unsupervised Visual Relations Discovery with Graph-level Analogy

Visual relations form the basis of understanding our compositional world...

6 Daniel Zeng, et al. ∙

research

∙ 06/30/2022

ZeroC: A Neuro-Symbolic Model for Zero-shot Concept Recognition and Acquisition at Inference Time

Humans have the remarkable ability to recognize and acquire novel visual...

5 Tailin Wu, et al. ∙

research

∙ 06/15/2022

Learning to Accelerate Partial Differential Equations via Latent Global Evolution

Simulating the time evolution of Partial Differential Equations (PDEs) o...

16 Tailin Wu, et al. ∙

research

∙ 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...

2 Tailin Wu, et al. ∙

research

∙ 06/07/2022

Learning Backward Compatible Embeddings

Embeddings, low-dimensional vector representation of objects, are fundam...

14 Weihua Hu, et al. ∙

research

∙ 05/24/2022

ItemSage: Learning Product Embeddings for Shopping Recommendations at Pinterest

Learned embeddings for products are an important building block for web-...

3 Paul Baltescu, et al. ∙

research

∙ 05/23/2022

VQA-GNN: Reasoning with Multimodal Semantic Graph for Visual Question Answering

Visual understanding requires seamless integration between recognition a...

12 Yanan Wang, et al. ∙

research

∙ 05/21/2022

MultiBiSage: A Web-Scale Recommendation System Using Multiple Bipartite Graphs at Pinterest

Graph Convolutional Networks (GCN) can efficiently integrate graph struc...

13 Saket Gurukar, et al. ∙

research

∙ 05/09/2022

PinnerFormer: Sequence Modeling for User Representation at Pinterest

Sequential models have become increasingly popular in powering personali...

2 Nikil Pancha, et al. ∙

research

∙ 03/30/2022

AdaGrid: Adaptive Grid Search for Link Prediction Training Objective

One of the most important factors that contribute to the success of a ma...

0 Tim Poštuvan, et al. ∙

research

∙ 03/29/2022

LinkBERT: Pretraining Language Models with Document Links

Language model (LM) pretraining can learn various knowledge from text co...

18 Michihiro Yasunaga, et al. ∙

research

∙ 01/21/2022

GreaseLM: Graph REASoning Enhanced Language Models for Question Answering

Answering complex questions about textual narratives requires reasoning ...

1 Xikun Zhang, et al. ∙

research

∙ 12/09/2021

Extending the WILDS Benchmark for Unsupervised Adaptation

Machine learning systems deployed in the wild are often trained on a sou...

17 Shiori Sagawa, et al. ∙

research

∙ 10/28/2021

Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Cones

Hierarchical relations are prevalent and indispensable for organizing hu...

6 Yushi Bai, et al. ∙

research

∙ 10/28/2021

SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs

Knowledge graphs (KGs) capture knowledge in the form of head–relation–ta...

6 Hongyu Ren, et al. ∙

research

∙ 09/20/2021

Neural Distance Embeddings for Biological Sequences

The development of data-dependent heuristics and representations for bio...

38 Gabriele Corso, et al. ∙

research

∙ 09/14/2021

LM-Critic: Language Models for Unsupervised Grammatical Error Correction

Training a model for grammatical error correction (GEC) requires a set o...

12 Michihiro Yasunaga, et al. ∙

research

∙ 07/12/2021

Combiner: Full Attention Transformer with Sparse Computation Cost

Transformers provide a class of expressive architectures that are extrem...

3 Hongyu Ren, et al. ∙

research

∙ 06/10/2021

GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings

We present GNNAutoScale (GAS), a framework for scaling arbitrary message...

9 Matthias Fey, et al. ∙

research

∙ 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...

15 Michihiro Yasunaga, et al. ∙

research

∙ 03/21/2021

Language-Agnostic Representation Learning of Source Code from Structure and Context

Source code (Context) and its parsed abstract syntax tree (AST; Structur...

5 Daniel Zügner, et al. ∙

research

∙ 03/17/2021

OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs

Enabling effective and efficient machine learning (ML) over large-scale ...

61 Weihua Hu, et al. ∙

research

∙ 03/02/2021

ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations

With massive amounts of atomic simulation data available, there is a hug...

54 Weihua Hu, et al. ∙

research

∙ 02/14/2021

Model-Agnostic Graph Regularization for Few-Shot Learning

In many domains, relationships between categories are encoded in the kno...

15 Ethan Shen, et al. ∙

research

∙ 02/10/2021

Driver2vec: Driver Identification from Automotive Data

With increasing focus on privacy protection, alternative methods to iden...

62 Jingbo Yang, et al. ∙

research

∙ 02/06/2021

Open-World Semi-Supervised Learning

Supervised and semi-supervised learning methods have been traditionally ...

3 Kaidi Cao, et al. ∙

Jure Leskovec

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