b'Renjie Liao'

research

∙ 08/25/2023

GEMTrans: A General, Echocardiography-based, Multi-Level Transformer Framework for Cardiovascular Diagnosis

Echocardiography (echo) is an ultrasound imaging modality that is widely...

0 Masoud Mokhtari, et al. ∙

research

∙ 07/23/2023

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

The functional assessment of the left ventricle chamber of the heart req...

0 Masoud Mokhtari, et al. ∙

research

∙ 06/03/2023

Memorization Capacity of Multi-Head Attention in Transformers

In this paper, we investigate the memorization capabilities of multi-hea...

0 Sadegh Mahdavi, et al. ∙

research

∙ 03/02/2023

Specformer: Spectral Graph Neural Networks Meet Transformers

Spectral graph neural networks (GNNs) learn graph representations via sp...

0 Deyu Bo, et al. ∙

research

∙ 02/02/2023

Self-Supervised Relation Alignment for Scene Graph Generation

The goal of scene graph generation is to predict a graph from an input i...

0 Bicheng Xu, et al. ∙

research

∙ 11/28/2022

GraphPNAS: Learning Distribution of Good Neural Architectures via Deep Graph Generative Models

Neural architectures can be naturally viewed as computational graphs. Mo...

0 Muchen Li, et al. ∙

research

∙ 10/24/2022

VLC-BERT: Visual Question Answering with Contextualized Commonsense Knowledge

There has been a growing interest in solving Visual Question Answering (...

0 Sahithya Ravi, et al. ∙

research

∙ 10/19/2022

Gaussian-Bernoulli RBMs Without Tears

We revisit the challenging problem of training Gaussian-Bernoulli restri...

5 Renjie Liao, et al. ∙

research

∙ 10/07/2022

Scaling Forward Gradient With Local Losses

Forward gradient learning computes a noisy directional gradient and is a...

8 Mengye Ren, et al. ∙

research

∙ 08/30/2022

EchoGNN: Explainable Ejection Fraction Estimation with Graph Neural Networks

Ejection fraction (EF) is a key indicator of cardiac function, allowing ...

8 Masoud Mokhtari, et al. ∙

research

∙ 07/20/2022

NeuralBF: Neural Bilateral Filtering for Top-down Instance Segmentation on Point Clouds

We introduce a method for instance proposal generation for 3D point clou...

9 Weiwei Sun, et al. ∙

research

∙ 06/25/2021

NP-DRAW: A Non-Parametric Structured Latent Variable Modelfor Image Generation

In this paper, we present a non-parametric structured latent variable mo...

17 Xiaohui Zeng, et al. ∙

research

∙ 01/17/2021

LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting

Forecasting the future behaviors of dynamic actors is an important task ...

42 Wenyuan Zeng, et al. ∙

research

∙ 01/16/2021

LookOut: Diverse Multi-Future Prediction and Planning for Self-Driving

Self-driving vehicles need to anticipate a diverse set of future traffic...

8 Alexander Cui, et al. ∙

research

∙ 01/07/2021

Safety-Oriented Pedestrian Motion and Scene Occupancy Forecasting

In this paper, we address the important problem in self-driving of forec...

19 Katie Luo, et al. ∙

research

∙ 12/14/2020

A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks

In this paper, we derive generalization bounds for the two primary class...

10 Renjie Liao, et al. ∙

research

∙ 12/13/2020

GeoNet++: Iterative Geometric Neural Network with Edge-Aware Refinement for Joint Depth and Surface Normal Estimation

In this paper, we propose a geometric neural network with edge-aware ref...

10 Xiaojuan Qi, et al. ∙

research

∙ 08/13/2020

DSDNet: Deep Structured self-Driving Network

In this paper, we propose the Deep Structured self-Driving Network (DSDN...

5 Wenyuan Zeng, et al. ∙

research

∙ 08/13/2020

Testing the Safety of Self-driving Vehicles by Simulating Perception and Prediction

We present a novel method for testing the safety of self-driving vehicle...

9 Kelvin Wong, et al. ∙

research

∙ 07/27/2020

Learning Lane Graph Representations for Motion Forecasting

We propose a motion forecasting model that exploits a novel structured m...

2 Ming Liang, et al. ∙

research

∙ 07/23/2020

Implicit Latent Variable Model for Scene-Consistent Motion Forecasting

In order to plan a safe maneuver an autonomous vehicle must accurately p...

5 Sergio Casas, et al. ∙

research

∙ 06/21/2020

Fast and Accurate: Structure Coherence Component for Face Alignment

In this paper, we propose a fast and accurate coordinate regression meth...

0 Beier Zhu, et al. ∙

research

∙ 02/15/2020

Latent Variable Modelling with Hyperbolic Normalizing Flows

The choice of approximate posterior distributions plays a central role i...

10 Avishek Joey Bose, et al. ∙

research

∙ 02/10/2020

Nonlinear Equation Solving: A Faster Alternative to Feedforward Computation

Feedforward computations, such as evaluating a neural network or samplin...

40 Yang Song, et al. ∙

research

∙ 10/18/2019

Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data

In this paper, we tackle the problem of relational behavior forecasting ...

31 Sergio Casas, et al. ∙

research

∙ 10/17/2019

Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction

Self-driving vehicles plan around both static and dynamic objects, apply...

21 Ajay Jain, et al. ∙

research

∙ 10/02/2019

Efficient Graph Generation with Graph Recurrent Attention Networks

We propose a new family of efficient and expressive deep generative mode...

16 Renjie Liao, et al. ∙

research

∙ 09/27/2019

DMM-Net: Differentiable Mask-Matching Network for Video Object Segmentation

In this paper, we propose the differentiable mask-matching network (DMM-...

8 Xiaohui Zeng, et al. ∙

research

∙ 07/30/2019

Deformable Filter Convolution for Point Cloud Reasoning

Point clouds are the native output of many real-world 3D sensors. To bor...

0 Yuwen Xiong, et al. ∙

research

∙ 06/22/2019

Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models

We introduce a new molecular dataset, named Alchemy, for developing mach...

15 Guangyong Chen, et al. ∙

research

∙ 05/15/2019

DARNet: Deep Active Ray Network for Building Segmentation

In this paper, we propose a Deep Active Ray Network (DARNet) for automat...

0 Dominic Cheng, et al. ∙

research

∙ 01/12/2019

UPSNet: A Unified Panoptic Segmentation Network

In this paper, we propose a unified panoptic segmentation network (UPSNe...

22 Yuwen Xiong, et al. ∙

research

∙ 01/06/2019

LanczosNet: Multi-Scale Deep Graph Convolutional Networks

We propose the Lanczos network (LanczosNet), which uses the Lanczos algo...

0 Renjie Liao, et al. ∙

research

∙ 10/16/2018

Incremental Few-Shot Learning with Attention Attractor Networks

Machine learning classifiers are often trained to recognize a set of pre...

0 Mengye Ren, et al. ∙

research

∙ 09/08/2018

Neural Guided Constraint Logic Programming for Program Synthesis

Synthesizing programs using example input/outputs is a classic problem i...

0 Lisa Zhang, et al. ∙

research

∙ 03/21/2018

Inference in Probabilistic Graphical Models by Graph Neural Networks

A useful computation when acting in a complex environment is to infer th...

0 KiJung Yoon, et al. ∙

research

∙ 03/16/2018

Reviving and Improving Recurrent Back-Propagation

In this paper, we revisit the recurrent back-propagation (RBP) algorithm...

0 Renjie Liao, et al. ∙

research

∙ 03/16/2018

Learning deep structured active contours end-to-end

The world is covered with millions of buildings, and precisely knowing e...

0 Diego Marcos, et al. ∙

research

∙ 03/16/2018

Graph Partition Neural Networks for Semi-Supervised Classification

We present graph partition neural networks (GPNN), an extension of graph...

0 Renjie Liao, et al. ∙

research

∙ 03/06/2018

Understanding Short-Horizon Bias in Stochastic Meta-Optimization

Careful tuning of the learning rate, or even schedules thereof, can be c...

0 Yuhuai Wu, et al. ∙

research

∙ 08/14/2017

Situation Recognition with Graph Neural Networks

We address the problem of recognizing situations in images. Given an ima...

0 Ruiyu Li, et al. ∙

research

∙ 04/10/2017

Detail-revealing Deep Video Super-resolution

Previous CNN-based video super-resolution approaches need to align multi...

0 Xin Tao, et al. ∙

research

∙ 11/14/2016

Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes

Normalization techniques have only recently begun to be exploited in sup...

0 Mengye Ren, et al. ∙

Renjie Liao

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