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LaneRCNN: Distributed Representations for Graph-Centric Motion Forecasting


Jan 17, 2021
Wenyuan Zeng, Ming Liang, Renjie Liao, Raquel Urtasun


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


Jan 16, 2021
Alexander Cui, Abbas Sadat, Sergio Casas, Renjie Liao, Raquel Urtasun


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Safety-Oriented Pedestrian Motion and Scene Occupancy Forecasting


Jan 07, 2021
Katie Luo, Sergio Casas, Renjie Liao, Xinchen Yan, Yuwen Xiong, Wenyuan Zeng, Raquel Urtasun


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


Dec 14, 2020
Renjie Liao, Raquel Urtasun, Richard Zemel


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


Dec 13, 2020
Xiaojuan Qi, Zhengzhe Liu, Renjie Liao, Philip H. S. Torr, Raquel Urtasun, Jiaya Jia

* TPAMI 2020. Code available: https://github.com/xjqi/GeoNet 

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DSDNet: Deep Structured self-Driving Network


Aug 13, 2020
Wenyuan Zeng, Shenlong Wang, Renjie Liao, Yun Chen, Bin Yang, Raquel Urtasun

* ECCV 2020 

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


Aug 13, 2020
Kelvin Wong, Qiang Zhang, Ming Liang, Bin Yang, Renjie Liao, Abbas Sadat, Raquel Urtasun

* ECCV 2020 

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Learning Lane Graph Representations for Motion Forecasting


Jul 27, 2020
Ming Liang, Bin Yang, Rui Hu, Yun Chen, Renjie Liao, Song Feng, Raquel Urtasun

* ECCV 2020 Oral 

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Implicit Latent Variable Model for Scene-Consistent Motion Forecasting


Jul 23, 2020
Sergio Casas, Cole Gulino, Simon Suo, Katie Luo, Renjie Liao, Raquel Urtasun

* European Conference on Computer Vision (ECCV) 2020 

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Fast and Accurate: Structure Coherence Component for Face Alignment


Jun 21, 2020
Beier Zhu, Chunze Lin, Quan Wang, Renjie Liao, Chen Qian


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Latent Variable Modelling with Hyperbolic Normalizing Flows


Feb 18, 2020
Avishek Joey Bose, Ariella Smofsky, Renjie Liao, Prakash Panangaden, William L. Hamilton

* Preprint, work under review 

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Nonlinear Equation Solving: A Faster Alternative to Feedforward Computation


Feb 10, 2020
Yang Song, Chenlin Meng, Renjie Liao, Stefano Ermon


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


Oct 18, 2019
Sergio Casas, Cole Gulino, Renjie Liao, Raquel Urtasun


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Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction


Oct 17, 2019
Ajay Jain, Sergio Casas, Renjie Liao, Yuwen Xiong, Song Feng, Sean Segal, Raquel Urtasun

* CoRL 2019 

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Efficient Graph Generation with Graph Recurrent Attention Networks


Oct 02, 2019
Renjie Liao, Yujia Li, Yang Song, Shenlong Wang, Charlie Nash, William L. Hamilton, David Duvenaud, Raquel Urtasun, Richard S. Zemel

* Neural Information Processing Systems (NeurIPS) 2019 

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


Sep 27, 2019
Xiaohui Zeng, Renjie Liao, Li Gu, Yuwen Xiong, Sanja Fidler, Raquel Urtasun

* ICCV 2019 

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Deformable Filter Convolution for Point Cloud Reasoning


Jul 30, 2019
Yuwen Xiong, Mengye Ren, Renjie Liao, Kelvin Wong, Raquel Urtasun


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Alchemy: A Quantum Chemistry Dataset for Benchmarking AI Models


Jun 22, 2019
Guangyong Chen, Pengfei Chen, Chang-Yu Hsieh, Chee-Kong Lee, Benben Liao, Renjie Liao, Weiwen Liu, Jiezhong Qiu, Qiming Sun, Jie Tang, Richard Zemel, Shengyu Zhang

* Authors are listed in alphabetical order 

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DARNet: Deep Active Ray Network for Building Segmentation


May 15, 2019
Dominic Cheng, Renjie Liao, Sanja Fidler, Raquel Urtasun

* CVPR 2019 

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UPSNet: A Unified Panoptic Segmentation Network


Jan 12, 2019
Yuwen Xiong, Renjie Liao, Hengshuang Zhao, Rui Hu, Min Bai, Ersin Yumer, Raquel Urtasun

* Technical report 

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LanczosNet: Multi-Scale Deep Graph Convolutional Networks


Jan 06, 2019
Renjie Liao, Zhizhen Zhao, Raquel Urtasun, Richard S. Zemel

* The International Conference on Learning Representations (ICLR) 2019 

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Neural Guided Constraint Logic Programming for Program Synthesis


Oct 26, 2018
Lisa Zhang, Gregory Rosenblatt, Ethan Fetaya, Renjie Liao, William E. Byrd, Matthew Might, Raquel Urtasun, Richard Zemel

* To appear in NIPS 2018 

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Incremental Few-Shot Learning with Attention Attractor Networks


Oct 16, 2018
Mengye Ren, Renjie Liao, Ethan Fetaya, Richard S. Zemel


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Reviving and Improving Recurrent Back-Propagation


Aug 13, 2018
Renjie Liao, Yuwen Xiong, Ethan Fetaya, Lisa Zhang, KiJung Yoon, Xaq Pitkow, Raquel Urtasun, Richard Zemel


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Inference in Probabilistic Graphical Models by Graph Neural Networks


May 25, 2018
KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard Zemel, Xaq Pitkow


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Learning deep structured active contours end-to-end


Mar 16, 2018
Diego Marcos, Devis Tuia, Benjamin Kellenberger, Lisa Zhang, Min Bai, Renjie Liao, Raquel Urtasun

* To appear, CVPR 2018 

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Graph Partition Neural Networks for Semi-Supervised Classification


Mar 16, 2018
Renjie Liao, Marc Brockschmidt, Daniel Tarlow, Alexander L. Gaunt, Raquel Urtasun, Richard Zemel


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Understanding Short-Horizon Bias in Stochastic Meta-Optimization


Mar 06, 2018
Yuhuai Wu, Mengye Ren, Renjie Liao, Roger Grosse

* 17 pages, 8 figures; To appear in ICLR2018 

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Situation Recognition with Graph Neural Networks


Aug 14, 2017
Ruiyu Li, Makarand Tapaswi, Renjie Liao, Jiaya Jia, Raquel Urtasun, Sanja Fidler

* ICCV2017 

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Detail-revealing Deep Video Super-resolution


Apr 10, 2017
Xin Tao, Hongyun Gao, Renjie Liao, Jue Wang, Jiaya Jia

* 9 pages, submitted to conference 

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