Search Results - "Tu, James"

Physically Realizable Adversarial Examples for LiDAR Object Detection by Tu, James, Ren, Mengye, Manivasagam, Sivabalan, Liang, Ming, Yang, Bin, Du, Richard, Cheng, Frank, Urtasun, Raquel

“…Modern autonomous driving systems rely heavily on deep learning models to process point cloud sensory data; meanwhile, deep models have been shown to be…”
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Analysis of bacterial diversity during the fermentation of inyu, a high-temperature fermented soy sauce, using nested PCR-denaturing gradient gel electrophoresis and the plate count method by Wei, Chia-Li, Chao, Shiou-Huei, Tsai, Wen-Bin, Lee, Pei-Shan, Tsau, Nai-Hung, Chen, Jhih-Shan, Lai, Wen-Lin, Ching-Yueh Tu, James, Tsai, Ying-Chieh

“…The diversity of bacteria associated with the fermentation of inyu, also known as black soy sauce, was studied through the nested PCR-denaturing gradient gel…”
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Spear: Optimized Dependency-Aware Task Scheduling with Deep Reinforcement Learning by Hu, Zhiming, Tu, James, Li, Baochun

“…Modern data parallel frameworks, such as Apache Spark, are designed to execute complex data processing jobs that contain a large number of tasks, with…”
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AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles by Wang, Jingkang, Pun, Ava, Tu, James, Manivasagam, Sivabalan, Sadat, Abbas, Casas, Sergio, Ren, Mengye, Urtasun, Raquel

“…As self-driving systems become better, simulating scenarios where the autonomy stack may fail becomes more important. Traditionally, those scenarios are…”
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Adversarial Attacks On Multi-Agent Communication by Tu, James, Wang, Tsunhsuan, Wang, Jingkang, Manivasagam, Sivabalan, Ren, Mengye, Urtasun, Raquel

“…Growing at a fast pace, modern autonomous systems will soon be deployed at scale, opening up the possibility for cooperative multi-agent systems. Sharing…”
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MIXSIM: A Hierarchical Framework for Mixed Reality Traffic Simulation by Suo, Simon, Wong, Kelvin, Xu, Justin, Tu, James, Cui, Alexander, Casas, Sergio, Urtasun, Raquel

“…The prevailing way to test a self-driving vehicle (SDV) in simulation involves non-reactive open-loop replay of real world scenarios. However, in order to…”
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Diverse Complexity Measures for Dataset Curation in Self-Driving by Sadat, Abbas, Segal, Sean, Casas, Sergio, Tu, James, Yang, Bin, Urtasun, Raquel, Yumer, Ersin

“…Modern self-driving systems heavily rely on deep learning. As a consequence, their performance is influenced significantly by the quality and richness of the…”
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Learning Realistic Traffic Agents in Closed-loop by Zhang, Chris, Tu, James, Zhang, Lunjun, Wong, Kelvin, Suo, Simon, Urtasun, Raquel

“…Realistic traffic simulation is crucial for developing self-driving software in a safe and scalable manner prior to real-world deployment. Typically, imitation…”
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Adv3D: Generating Safety-Critical 3D Objects through Closed-Loop Simulation by Sarva, Jay, Wang, Jingkang, Tu, James, Xiong, Yuwen, Manivasagam, Sivabalan, Urtasun, Raquel

“…Self-driving vehicles (SDVs) must be rigorously tested on a wide range of scenarios to ensure safe deployment. The industry typically relies on closed-loop…”
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Learning to Communicate and Correct Pose Errors by Vadivelu, Nicholas, Ren, Mengye, Tu, James, Wang, Jingkang, Urtasun, Raquel

“…Learned communication makes multi-agent systems more effective by aggregating distributed information. However, it also exposes individual agents to the threat…”
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Identification of Potential Molecular Targets for Directed Thrombosis after Radiosurgery in an Animal Arteriovenous Malformation Model: Paper 22 by Storer, Kingsley P., Karunanayaka, Athula, Tu, James, Smee, Robert, Watling, Amy, Stoodley, Marcus A.

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Identification of Potential Molecular Targets for Directed Thrombosis after Radiosurgery in an Animal Arteriovenous Malformation Model: Paper 22 by Storer, Kingsley P., Karunanayaka, Athula, Tu, James, Smee, Robert, Watling, Amy, Stoodley, Marcus A.

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3D Reasoning for Unsupervised Anomaly Detection in Pediatric WbMRI by Chang, Alex, Suriyakumar, Vinith, Moturu, Abhishek, Tu, James, Tewattanarat, Nipaporn, Joshi, Sayali, Doria, Andrea, Goldenberg, Anna

“…Modern deep unsupervised learning methods have shown great promise for detecting diseases across a variety of medical imaging modalities. While previous…”
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Adversarial Attacks On Multi-Agent Communication by Tu, James, Wang, Tsunhsuan, Wang, Jingkang, Manivasagam, Sivabalan, Ren, Mengye, Urtasun, Raquel

“…International Conference On Computer Vision 2021 Growing at a fast pace, modern autonomous systems will soon be deployed at scale, opening up the possibility…”
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AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles by Wang, Jingkang, Pun, Ava, Tu, James, Manivasagam, Sivabalan, Sadat, Abbas, Casas, Sergio, Ren, Mengye, Urtasun, Raquel

“…As self-driving systems become better, simulating scenarios where the autonomy stack may fail becomes more important. Traditionally, those scenarios are…”
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Diverse Complexity Measures for Dataset Curation in Self-driving by Sadat, Abbas, Segal, Sean, Casas, Sergio, Tu, James, Yang, Bin, Urtasun, Raquel, Yumer, Ersin

“…Modern self-driving autonomy systems heavily rely on deep learning. As a consequence, their performance is influenced significantly by the quality and richness…”
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StrObe: Streaming Object Detection from LiDAR Packets by Frossard, Davi, Suo, Simon, Casas, Sergio, Tu, James, Hu, Rui, Urtasun, Raquel

“…Many modern robotics systems employ LiDAR as their main sensing modality due to its geometrical richness. Rolling shutter LiDARs are particularly common, in…”
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V2VNet: Vehicle-to-Vehicle Communication for Joint Perception and Prediction by Wang, Tsun-Hsuan, Manivasagam, Sivabalan, Liang, Ming, Yang, Bin, Zeng, Wenyuan, Tu, James, Urtasun, Raquel

“…In this paper, we explore the use of vehicle-to-vehicle (V2V) communication to improve the perception and motion forecasting performance of self-driving…”
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Physically Realizable Adversarial Examples for LiDAR Object Detection by Tu, James, Ren, Mengye, Manivasagam, Siva, Liang, Ming, Yang, Bin, Du, Richard, Cheng, Frank, Urtasun, Raquel

“…Modern autonomous driving systems rely heavily on deep learning models to process point cloud sensory data; meanwhile, deep models have been shown to be…”
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Exploring Adversarial Robustness of Multi-Sensor Perception Systems in Self Driving by Tu, James, Li, Huichen, Yan, Xinchen, Ren, Mengye, Chen, Yun, Liang, Ming, Bitar, Eilyan, Yumer, Ersin, Urtasun, Raquel

“…Modern self-driving perception systems have been shown to improve upon processing complementary inputs such as LiDAR with images. In isolation, 2D images have…”
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