Yue Wang

According to our database, Yue Wang authored at least 33 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Tokenize the World into Object-level Knowledge to Address Long-tail Events in Autonomous Driving.

Ran Tian, Boyi Li, Xinshuo Weng, Yuxiao Chen, Edward Schmerling, Yue Wang, Boris Ivanovic, Marco Pavone

CoRR, 2024

DistillNeRF: Perceiving 3D Scenes from Single-Glance Images by Distilling Neural Fields and Foundation Model Features.

Letian Wang, Seung Wook Kim, Jiawei Yang, Cunjun Yu, Boris Ivanovic, Steven L. Waslander, Yue Wang, Sanja Fidler, Marco Pavone, Péter Karkus

CoRR, 2024

Memorize What Matters: Emergent Scene Decomposition from Multitraverse.

Yiming Li, Zehong Wang, Yue Wang, Zhiding Yu, Zan Gojcic, Marco Pavone, Chen Feng, José M. Álvarez

CoRR, 2024

Language-Image Models with 3D Understanding.

Jang Hyun Cho, Boris Ivanovic, Yulong Cao, Edward Schmerling, Yue Wang, Xinshuo Weng, Boyi Li, Yurong You, Philipp Krähenbühl, Yan Wang, Marco Pavone

CoRR, 2024

InstantSplat: Unbounded Sparse-view Pose-free Gaussian Splatting in 40 Seconds.

Zhiwen Fan, Wenyan Cong, Kairun Wen, Kevin Wang, Jian Zhang, Xinghao Ding, Danfei Xu, Boris Ivanovic, Marco Pavone, Georgios Pavlakos, Zhangyang Wang, Yue Wang

CoRR, 2024

Q-SLAM: Quadric Representations for Monocular SLAM.

Chensheng Peng, Chenfeng Xu, Yue Wang, Mingyu Ding, Heng Yang, Masayoshi Tomizuka, Kurt Keutzer, Marco Pavone, Wei Zhan

CoRR, 2024

Parallelized Spatiotemporal Binding.

Gautam Singh, Yue Wang, Jiawei Yang, Boris Ivanovic, Sungjin Ahn, Marco Pavone, Tong Che

CoRR, 2024

Driving Everywhere with Large Language Model Policy Adaptation.

Boyi Li, Yue Wang, Jiageng Mao, Boris Ivanovic, Sushant Veer, Karen Leung, Marco Pavone

CoRR, 2024

Denoising Vision Transformers.

Jiawei Yang, Katie Z. Luo, Jiefeng Li, Kilian Q. Weinberger, Yonglong Tian, Yue Wang

CoRR, 2024

Augmenting Lane Perception and Topology Understanding with Standard Definition Navigation Maps.

Katie Z. Luo, Xinshuo Weng, Yan Wang, Shuang Wu, Jie Li, Kilian Q. Weinberger, Yue Wang, Marco Pavone

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

EmerNeRF: Emergent Spatial-Temporal Scene Decomposition via Self-Supervision.

Jiawei Yang, Boris Ivanovic, Or Litany, Xinshuo Weng, Seung Wook Kim, Boyi Li, Tong Che, Danfei Xu, Sanja Fidler, Marco Pavone, Yue Wang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

SmartDeal: Remodeling Deep Network Weights for Efficient Inference and Training.

Xiaohan Chen, Yang Zhao, Yue Wang, Pengfei Xu, Haoran You, Chaojian Li, Yonggan Fu, Yingyan Lin, Zhangyang Wang

IEEE Trans. Neural Networks Learn. Syst., October, 2023

A Language Agent for Autonomous Driving.

Jiageng Mao, Junjie Ye, Yuxi Qian, Marco Pavone, Yue Wang

CoRR, 2023

SSCBench: A Large-Scale 3D Semantic Scene Completion Benchmark for Autonomous Driving.

Yiming Li, Sihang Li, Xinhao Liu, Moonjun Gong, Kenan Li, Nuo Chen, Zijun Wang, Zhiheng Li, Tao Jiang, Fisher Yu, Yue Wang, Hang Zhao, Zhiding Yu, Chen Feng

CoRR, 2023

FreeNeRF: Improving Few-Shot Neural Rendering with Free Frequency Regularization.

Jiawei Yang, Marco Pavone, Yue Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Multi-Robot Scene Completion: Towards Task-Agnostic Collaborative Perception.

Yiming Li, Juexiao Zhang, Dekun Ma, Yue Wang, Chen Feng

Proceedings of the Conference on Robot Learning, 2022

2021

HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark.

Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Yingyan Lin

CoRR, 2021

SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training.

Xiaohan Chen, Yang Zhao, Yue Wang, Pengfei Xu, Haoran You, Chaojian Li, Yonggan Fu, Yingyan Lin, Zhangyang Wang

CoRR, 2021

HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark.

Chaojian Li, Zhongzhi Yu, Yonggan Fu, Yongan Zhang, Yang Zhao, Haoran You, Qixuan Yu, Yue Wang, Cong Hao, Yingyan Lin

Proceedings of the 9th International Conference on Learning Representations, 2021

SACoD: Sensor Algorithm Co-Design Towards Efficient CNN-powered Intelligent PhlatCam.

Yonggan Fu, Yang Zhang, Yue Wang, Zhihan Lu, Vivek Boominathan, Ashok Veeraraghavan, Yingyan Lin

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Dual Dynamic Inference: Enabling More Efficient, Adaptive, and Controllable Deep Inference.

Yue Wang, Jianghao Shen, Ting-Kuei Hu, Pengfei Xu, Tan M. Nguyen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin

IEEE J. Sel. Top. Signal Process., 2020

FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training.

Yonggan Fu, Haoran You, Yang Zhao, Yue Wang, Chaojian Li, Kailash Gopalakrishnan, Zhangyang Wang, Yingyan Lin

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

A New MRAM-Based Process In-Memory Accelerator for Efficient Neural Network Training with Floating Point Precision.

Hongjie Wang, Yang Zhao, Chaojian Li, Yue Wang, Yingyan Lin

Proceedings of the IEEE International Symposium on Circuits and Systems, 2020

SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation.

Yang Zhao, Xiaohan Chen, Yue Wang, Chaojian Li, Haoran You, Yonggan Fu, Yuan Xie, Zhangyang Wang, Yingyan Lin

Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020

Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks.

Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Richard G. Baraniuk, Zhangyang Wang, Yingyan Lin

Proceedings of the 8th International Conference on Learning Representations, 2020

DNN-Chip Predictor: An Analytical Performance Predictor for DNN Accelerators with Various Dataflows and Hardware Architectures.

Yang Zhao, Chaojian Li, Yue Wang, Pengfei Xu, Yongan Zhang, Yingyan Lin

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

AutoDNNchip: An Automated DNN Chip Predictor and Builder for Both FPGAs and ASICs.

Pengfei Xu, Xiaofan Zhang, Cong Hao, Yang Zhao, Yongan Zhang, Yue Wang, Chaojian Li, Zetong Guan, Deming Chen, Yingyan Lin

Proceedings of the FPGA '20: The 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2020

Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference.

Jianghao Shen, Yue Wang, Pengfei Xu, Yonggan Fu, Zhangyang Wang, Yingyan Lin

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving.

Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao, Yingyan Lin, Zhangyang Wang

CoRR, 2019

Drawing early-bird tickets: Towards more efficient training of deep networks.

Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Yingyan Lin, Zhangyang Wang, Richard G. Baraniuk

CoRR, 2019

E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings.

Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao, Yingyan Lin, Zhangyang Wang

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Live Demonstration: Bringing Powerful Deep Learning into Daily-Life Devices (Mobiles and FPGAs) Via Deep k-Means.

Pengfei Xu, Yue Wang, Yang Zhao, Yingyan Lin

Proceedings of the IEEE International Symposium on Circuits and Systems, 2019

2018

Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions.

Junru Wu, Yue Wang, Zhenyu Wu, Zhangyang Wang, Ashok Veeraraghavan, Yingyan Lin

Proceedings of the 35th International Conference on Machine Learning, 2018