Hongyu Ren | DeepAI

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Jure Leskovec
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Ce Zhang
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Dorsa Sadigh
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∙ 08/12/2023

Approximate Answering of Graph Queries

Knowledge graphs (KGs) are inherently incomplete because of incomplete w...

0 Michael Cochez, et al. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 11/16/2022

Holistic Evaluation of Language Models

Language models (LMs) are becoming the foundation for almost all major l...

21 Percy Liang, et al. ∙

∙ 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. ∙

∙ 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. ∙

∙ 10/13/2022

Inductive Logical Query Answering in Knowledge Graphs

Formulating and answering logical queries is a standard communication in...

0 Mikhail Galkin, et al. ∙

∙ 10/04/2022

TripleE: Easy Domain Generalization via Episodic Replay

Learning how to generalize the model to unseen domains is an important a...

9 Xiaomeng Li, et al. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 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. ∙

∙ 10/24/2020

Graph Information Bottleneck

Representation learning of graph-structured data is challenging because ...

20 Tailin Wu, et al. ∙

∙ 10/22/2020

Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge Graphs

One of the fundamental problems in Artificial Intelligence is to perform...

23 Hongyu Ren, et al. ∙

∙ 08/17/2020

OCEAN: Online Task Inference for Compositional Tasks with Context Adaptation

Real-world tasks often exhibit a compositional structure that contains a...

1 Hongyu Ren, et al. ∙

∙ 05/02/2020

Open Graph Benchmark: Datasets for Machine Learning on Graphs

We present the Open Graph Benchmark (OGB), a diverse set of challenging ...

64 Weihua Hu, et al. ∙

∙ 02/17/2020

Entity Context and Relational Paths for Knowledge Graph Completion

Knowledge graph completion aims to predict missing relations between ent...

7 Hongwei Wang, et al. ∙

∙ 02/14/2020

Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddings

Answering complex logical queries on large-scale incomplete knowledge gr...

12 Hongyu Ren, et al. ∙

∙ 11/08/2018

Bias and Generalization in Deep Generative Models: An Empirical Study

In high dimensional settings, density estimation algorithms rely crucial...

6 Shengjia Zhao, et al. ∙

∙ 07/26/2018

Multi-Agent Generative Adversarial Imitation Learning

Imitation learning algorithms can be used to learn a policy from expert ...

0 Jiaming Song, et al. ∙

∙ 05/27/2018

Adversarial Constraint Learning for Structured Prediction

Constraint-based learning reduces the burden of collecting labels by hav...

0 Hongyu Ren, et al. ∙

∙ 12/14/2017

RAN4IQA: Restorative Adversarial Nets for No-Reference Image Quality Assessment

Inspired by the free-energy brain theory, which implies that human visua...

0 Hongyu Ren, et al. ∙

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