Renjie Liao

Renjie Liao

University of Toronto

H-index: 38

North America-Canada

About Renjie Liao

Renjie Liao, With an exceptional h-index of 38 and a recent h-index of 36 (since 2020), a distinguished researcher at University of Toronto, specializes in the field of Machine Learning, Computer Vision, Artificial Intelligence.

His recent articles reflect a diverse array of research interests and contributions to the field:

Self-supervised relation alignment for scene graph generation

Revisiting the Equivalence of In-Context Learning and Gradient Descent: The Impact of Data Distribution

An Information-Theoretic Framework for Out-of-Distribution Generalization

Systems and Methods for Latent Distribution Modeling for Scene-Consistent Motion Forecasting

Generative 3D Part Assembly via Part-Whole-Hierarchy Message Passing

Joint Generative Modeling of Scene Graphs and Images via Diffusion Models

Neuralbf: Neural bilateral filtering for top-down instance segmentation on point clouds

Memorization capacity of multi-head attention in transformers

Renjie Liao Information

University

Position

___

Citations(all)

7003

Citations(since 2020)

6318

Cited By

2696

hIndex(all)

38

hIndex(since 2020)

36

i10Index(all)

54

i10Index(since 2020)

48

Email

University Profile Page

Google Scholar

Renjie Liao Skills & Research Interests

Machine Learning

Computer Vision

Artificial Intelligence

Top articles of Renjie Liao

Title

Journal

Author(s)

Publication Date

Self-supervised relation alignment for scene graph generation

Bicheng Xu

Renjie Liao

Leonid Sigal

2024

Revisiting the Equivalence of In-Context Learning and Gradient Descent: The Impact of Data Distribution

Sadegh Mahdavi

Renjie Liao

Christos Thrampoulidis

2024/4/14

An Information-Theoretic Framework for Out-of-Distribution Generalization

arXiv preprint arXiv:2403.19895

Wenliang Liu

Guanding Yu

Lele Wang

Renjie Liao

2024/3/29

Systems and Methods for Latent Distribution Modeling for Scene-Consistent Motion Forecasting

2023/12/12

Generative 3D Part Assembly via Part-Whole-Hierarchy Message Passing

arXiv preprint arXiv:2402.17464

Bi'an Du

Xiang Gao

Wei Hu

Renjie Liao

2024/2/27

Joint Generative Modeling of Scene Graphs and Images via Diffusion Models

arXiv preprint arXiv:2401.01130

Bicheng Xu

Qi Yan

Renjie Liao

Lele Wang

Leonid Sigal

2024/1/2

Neuralbf: Neural bilateral filtering for top-down instance segmentation on point clouds

Weiwei Sun

Daniel Rebain

Renjie Liao

Vladimir Tankovich

Soroosh Yazdani

...

2023

Memorization capacity of multi-head attention in transformers

arXiv preprint arXiv:2306.02010

Sadegh Mahdavi

Renjie Liao

Christos Thrampoulidis

2023/6/3

Vlc-bert: Visual question answering with contextualized commonsense knowledge

Sahithya Ravi

Aditya Chinchure

Leonid Sigal

Renjie Liao

Vered Shwartz

2023

GraphPNAS: Learning Probabilistic Graph Generators for Neural Architecture Search

Transactions on Machine Learning Research

Muchen Li

Jeffrey Yunfan Liu

Leonid Sigal

Renjie Liao

2023/5/23

Systems and Methods for Actor Motion Forecasting within a Surrounding Environment of an Autonomous Vehicle

2023/11/2

Systems and methods for generating motion forecast data for actors with respect to an autonomous vehicle and training a machine learned model for the same

2024/1/11

Gemtrans: A general, echocardiography-based, multi-level transformer framework for cardiovascular diagnosis

Masoud Mokhtari

Neda Ahmadi

Teresa SM Tsang

Purang Abolmaesumi

Renjie Liao

2023/10/8

Deep learning analysis of endometrial histology as a promising tool to predict the chance of pregnancy after frozen embryo transfers

Journal of Assisted Reproduction and Genetics

Tiantian Li

Renjie Liao

Crystal Chan

Ellen M Greenblatt

2023/4

EchoGLAD: Hierarchical Graph Neural Networks for Left Ventricle Landmark Detection on Echocardiograms

Masoud Mokhtari

Mobina Mahdavi

Hooman Vaseli

Christina Luong

Purang Abolmaesumi

...

2023/10/1

Specformer: Spectral graph neural networks meet transformers

The Eleventh International Conference on Learning Representations

Deyu Bo

Chuan Shi

Lele Wang

Renjie Liao

2023/3/2

Swingnn: Rethinking permutation invariance in diffusion models for graph generation

arXiv preprint arXiv:2307.01646

Qi Yan

Zhengyang Liang

Yang Song

Renjie Liao

Lele Wang

2023/7/4

Graph neural networks: graph generation

Graph Neural Networks: Foundations, Frontiers, and Applications

Renjie Liao

2022

Towards better out-of-distribution generalization of neural algorithmic reasoning tasks

Transactions on Machine Learning Research (TMLR)

Sadegh Mahdavi

Kevin Swersky

Thomas Kipf

Milad Hashemi

Christos Thrampoulidis

...

2022/11/1

Graph neural networks for node classification

Graph Neural Networks: Foundations, Frontiers, and Applications

Jian Tang

Renjie Liao

2022

See List of Professors in Renjie Liao University(University of Toronto)

Co-Authors

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