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2020 – today
- 2024
[c34]Jiachen Zhao, Zhun Deng, David Madras, James Zou, Mengye Ren:
Learning and Forgetting Unsafe Examples in Large Language Models. ICML 2024- [i47]A. Emin Orhan, Wentao Wang, Alex N. Wang, Mengye Ren, Brenden M. Lake:
Self-supervised learning of video representations from a child's perspective. CoRR abs/2402.00300 (2024) - [i46]Yanlai Yang, Matt Jones, Michael C. Mozer, Mengye Ren:
Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured training. CoRR abs/2403.09613 (2024) - [i45]Ryan Teehan, Brenden M. Lake, Mengye Ren:
CoLLEGe: Concept Embedding Generation for Large Language Models. CoRR abs/2403.15362 (2024) - [i44]Yipeng Zhang, Laurent Charlin, Richard S. Zemel, Mengye Ren:
Integrating Present and Past in Unsupervised Continual Learning. CoRR abs/2404.19132 (2024) - [i43]Jack Lu, Ryan Teehan, Mengye Ren:
ProCreate, Don't Reproduce! Propulsive Energy Diffusion for Creative Generation. CoRR abs/2408.02226 (2024) - [i42]Alex N. Wang, Christopher Hoang, Yuwen Xiong, Yann LeCun, Mengye Ren:
PooDLe: Pooled and dense self-supervised learning from naturalistic videos. CoRR abs/2408.11208 (2024) - 2023
- [c33]David Mayo, Tyler R. Scott, Mengye Ren, Gamaledin Elsayed, Katherine L. Hermann, Matt Jones, Michael Mozer:
Multitask Learning Via Interleaving: A Neural Network Investigation. CogSci 2023 - [c32]Lunjun Zhang, Anqi Joyce Yang, Yuwen Xiong, Sergio Casas, Bin Yang, Mengye Ren, Raquel Urtasun:
Towards Unsupervised Object Detection from LiDAR Point Clouds. CVPR 2023: 9317-9328 - [c31]Matt Jones, Tyler R. Scott, Mengye Ren, Gamaleldin Fathy Elsayed, Katherine L. Hermann, David Mayo, Michael Curtis Mozer:
Learning in temporally structured environments. ICLR 2023 - [c30]Mengye Ren, Simon Kornblith, Renjie Liao, Geoffrey E. Hinton:
Scaling Forward Gradient With Local Losses. ICLR 2023 - [i41]Chris Zhang, Runsheng Guo, Wenyuan Zeng, Yuwen Xiong, Binbin Dai, Rui Hu, Mengye Ren, Raquel Urtasun:
Rethinking Closed-loop Training for Autonomous Driving. CoRR abs/2306.15713 (2023) - [i40]Lunjun Zhang, Anqi Joyce Yang, Yuwen Xiong, Sergio Casas, Bin Yang, Mengye Ren, Raquel Urtasun:
Towards Unsupervised Object Detection From LiDAR Point Clouds. CoRR abs/2311.02007 (2023) - [i39]Yixuan Luo, Mengye Ren, Sai Qian Zhang:
BIM: Block-Wise Self-Supervised Learning with Masked Image Modeling. CoRR abs/2311.17218 (2023) - [i38]Ying Wang, Yanlai Yang, Mengye Ren:
LifelongMemory: Leveraging LLMs for Answering Queries in Egocentric Videos. CoRR abs/2312.05269 (2023) - [i37]Jiachen Zhao, Zhun Deng, David Madras, James Zou, Mengye Ren:
Learning and Forgetting Unsafe Examples in Large Language Models. CoRR abs/2312.12736 (2023) - 2022
- [c29]Chris Zhang, Runsheng Guo, Wenyuan Zeng, Yuwen Xiong, Binbin Dai, Rui Hu, Mengye Ren, Raquel Urtasun:
Rethinking Closed-Loop Training for Autonomous Driving. ECCV (39) 2022: 264-282 - [i36]Andrew Joohun Nam, Mengye Ren, Chelsea Finn, James L. McClelland:
Learning to Reason With Relational Abstractions. CoRR abs/2210.02615 (2022) - [i35]Mengye Ren, Simon Kornblith, Renjie Liao, Geoffrey E. Hinton:
Scaling Forward Gradient With Local Losses. CoRR abs/2210.03310 (2022) - [i34]Renjie Liao, Simon Kornblith, Mengye Ren, David J. Fleet, Geoffrey E. Hinton:
Gaussian-Bernoulli RBMs Without Tears. CoRR abs/2210.10318 (2022) - 2021
- [c28]Sean Segal, Nishanth Kumar, Sergio Casas, Wenyuan Zeng, Mengye Ren, Jingkang Wang, Raquel Urtasun:
Just Label What You Need: Fine-Grained Active Selection for P&P through Partially Labeled Scenes. CoRL 2021: 816-826 - [c27]James Tu, Huichen Li, Xinchen Yan, Mengye Ren, Yun Chen, Ming Liang, Eilyan Bitar, Ersin Yumer, Raquel Urtasun:
Exploring Adversarial Robustness of Multi-sensor Perception Systems in Self Driving. CoRL 2021: 1013-1024 - [c26]Shuhan Tan, Kelvin Wong, Shenlong Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun:
SceneGen: Learning To Generate Realistic Traffic Scenes. CVPR 2021: 892-901 - [c25]Jingkang Wang, Ava Pun, James Tu, Sivabalan Manivasagam, Abbas Sadat, Sergio Casas, Mengye Ren, Raquel Urtasun:
AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles. CVPR 2021: 9909-9918 - [c24]James Tu, Tsun-Hsuan Wang, Jingkang Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun:
Adversarial Attacks On Multi-Agent Communication. ICCV 2021: 7748-7757 - [c23]Yuwen Xiong, Mengye Ren, Wenyuan Zeng, Raquel Urtasun Waabi:
Self-Supervised Representation Learning from Flow Equivariance. ICCV 2021: 10171-10180 - [c22]James Lucas, Mengye Ren, Irene Raissa Kameni, Toniann Pitassi, Richard S. Zemel:
Theoretical bounds on estimation error for meta-learning. ICLR 2021 - [c21]Mengye Ren, Michael Louis Iuzzolino, Michael Curtis Mozer, Richard S. Zemel:
Wandering within a world: Online contextualized few-shot learning. ICLR 2021 - [c20]Alexander Wang, Mengye Ren, Richard S. Zemel:
SketchEmbedNet: Learning Novel Concepts by Imitating Drawings. ICML 2021: 10870-10881 - [c19]Bob Wei, Mengye Ren, Wenyuan Zeng, Ming Liang, Bin Yang, Raquel Urtasun:
Perceive, Attend, and Drive: Learning Spatial Attention for Safe Self-Driving. ICRA 2021: 4875-4881 - [i33]Shuhan Tan, Kelvin Wong, Shenlong Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun:
SceneGen: Learning to Generate Realistic Traffic Scenes. CoRR abs/2101.06541 (2021) - [i32]Jingkang Wang, Ava Pun, James Tu, Sivabalan Manivasagam, Abbas Sadat, Sergio Casas, Mengye Ren, Raquel Urtasun:
AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles. CoRR abs/2101.06549 (2021) - [i31]Yuwen Xiong, Mengye Ren, Wenyuan Zeng, Raquel Urtasun:
Self-Supervised Representation Learning from Flow Equivariance. CoRR abs/2101.06553 (2021) - [i30]James Tu, Tsun-Hsuan Wang, Jingkang Wang, Sivabalan Manivasagam, Mengye Ren, Raquel Urtasun:
Adversarial Attacks On Multi-Agent Communication. CoRR abs/2101.06560 (2021) - [i29]Jingkang Wang, Mengye Ren, Ilija Bogunovic, Yuwen Xiong, Raquel Urtasun:
Cost-Efficient Online Hyperparameter Optimization. CoRR abs/2101.06590 (2021) - [i28]James Tu, Huichen Li, Xinchen Yan, Mengye Ren, Yun Chen, Ming Liang, Eilyan Bitar, Ersin Yumer, Raquel Urtasun:
Exploring Adversarial Robustness of Multi-Sensor Perception Systems in Self Driving. CoRR abs/2101.06784 (2021) - [i27]Sean Segal, Nishanth Kumar, Sergio Casas, Wenyuan Zeng, Mengye Ren, Jingkang Wang, Raquel Urtasun:
Just Label What You Need: Fine-Grained Active Selection for Perception and Prediction through Partially Labeled Scenes. CoRR abs/2104.03956 (2021) - [i26]Mengye Ren, Tyler R. Scott, Michael L. Iuzzolino, Michael C. Mozer, Richard S. Zemel:
Online Unsupervised Learning of Visual Representations and Categories. CoRR abs/2109.05675 (2021) - 2020
- [c18]Nicholas Vadivelu, Mengye Ren, James Tu, Jingkang Wang, Raquel Urtasun:
Learning to Communicate and Correct Pose Errors. CoRL 2020: 1195-1210 - [c17]James Tu, Mengye Ren, Sivabalan Manivasagam, Ming Liang, Bin Yang, Richard Du, Frank Cheng, Raquel Urtasun:
Physically Realizable Adversarial Examples for LiDAR Object Detection. CVPR 2020: 13713-13722 - [c16]Abbas Sadat, Sergio Casas, Mengye Ren, Xinyu Wu, Pranaab Dhawan, Raquel Urtasun:
Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations. ECCV (23) 2020: 414-430 - [c15]Quinlan Sykora, Mengye Ren, Raquel Urtasun:
Multi-Agent Routing Value Iteration Network. ICML 2020: 9300-9310 - [c14]Lingyun Luke Li, Bin Yang, Ming Liang, Wenyuan Zeng, Mengye Ren, Sean Segal, Raquel Urtasun:
End-to-end Contextual Perception and Prediction with Interaction Transformer. IROS 2020: 5784-5791 - [c13]Yuwen Xiong, Mengye Ren, Raquel Urtasun:
LoCo: Local Contrastive Representation Learning. NeurIPS 2020 - [i25]James Tu, Mengye Ren, Siva Manivasagam, Ming Liang, Bin Yang, Richard Du, Frank Cheng, Raquel Urtasun:
Physically Realizable Adversarial Examples for LiDAR Object Detection. CoRR abs/2004.00543 (2020) - [i24]Mengye Ren, Michael L. Iuzzolino, Michael C. Mozer, Richard S. Zemel:
Wandering Within a World: Online Contextualized Few-Shot Learning. CoRR abs/2007.04546 (2020) - [i23]Quinlan Sykora, Mengye Ren, Raquel Urtasun:
Multi-Agent Routing Value Iteration Network. CoRR abs/2007.05096 (2020) - [i22]Yuwen Xiong, Mengye Ren, Raquel Urtasun:
LoCo: Local Contrastive Representation Learning. CoRR abs/2008.01342 (2020) - [i21]Lingyun Luke Li, Bin Yang, Ming Liang, Wenyuan Zeng, Mengye Ren, Sean Segal, Raquel Urtasun:
End-to-end Contextual Perception and Prediction with Interaction Transformer. CoRR abs/2008.05927 (2020) - [i20]Abbas Sadat, Sergio Casas, Mengye Ren, Xinyu Wu, Pranaab Dhawan, Raquel Urtasun:
Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations. CoRR abs/2008.05930 (2020) - [i19]Alexander Wang, Mengye Ren, Richard S. Zemel:
SketchEmbedNet: Learning Novel Concepts by Imitating Drawings. CoRR abs/2009.04806 (2020) - [i18]James Lucas, Mengye Ren, Irene Kameni, Toniann Pitassi, Richard S. Zemel:
Theoretical bounds on estimation error for meta-learning. CoRR abs/2010.07140 (2020) - [i17]Bob Wei, Mengye Ren, Wenyuan Zeng, Ming Liang, Bin Yang, Raquel Urtasun:
Perceive, Attend, and Drive: Learning Spatial Attention for Safe Self-Driving. CoRR abs/2011.01153 (2020) - [i16]Nicholas Vadivelu, Mengye Ren, James Tu, Jingkang Wang, Raquel Urtasun:
Learning to Communicate and Correct Pose Errors. CoRR abs/2011.05289 (2020) - [i15]Mengye Ren, Eleni Triantafillou, Kuan-Chieh Wang, James Lucas, Jake Snell, Xaq Pitkow, Andreas S. Tolias, Richard S. Zemel:
Flexible Few-Shot Learning with Contextual Similarity. CoRR abs/2012.05895 (2020)
2010 – 2019
- 2019
- [c12]Kelvin Wong, Shenlong Wang, Mengye Ren, Ming Liang, Raquel Urtasun:
Identifying Unknown Instances for Autonomous Driving. CoRL 2019: 384-393 - [c11]Chris Zhang, Mengye Ren, Raquel Urtasun:
Graph HyperNetworks for Neural Architecture Search. ICLR (Poster) 2019 - [c10]Abbas Sadat, Mengye Ren, Andrei Pokrovsky, Yen-Chen Lin, Ersin Yumer, Raquel Urtasun:
Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehicles. IROS 2019: 3949-3956 - [c9]Mengye Ren, Renjie Liao, Ethan Fetaya, Richard S. Zemel:
Incremental Few-Shot Learning with Attention Attractor Networks. NeurIPS 2019: 5276-5286 - [i14]Yuwen Xiong, Mengye Ren, Renjie Liao, Kelvin Wong, Raquel Urtasun:
Deformable Filter Convolution for Point Cloud Reasoning. CoRR abs/1907.13079 (2019) - [i13]Abbas Sadat, Mengye Ren, Andrei Pokrovsky, Yen-Chen Lin, Ersin Yumer, Raquel Urtasun:
Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehicles. CoRR abs/1910.04586 (2019) - [i12]Yuwen Xiong, Mengye Ren, Raquel Urtasun:
Learning to Remember from a Multi-Task Teacher. CoRR abs/1910.04650 (2019) - [i11]Kelvin Wong, Shenlong Wang, Mengye Ren, Ming Liang, Raquel Urtasun:
Identifying Unknown Instances for Autonomous Driving. CoRR abs/1910.11296 (2019) - 2018
- [c8]Mengye Ren, Andrei Pokrovsky, Bin Yang, Raquel Urtasun:
SBNet: Sparse Blocks Network for Fast Inference. CVPR 2018: 8711-8720 - [c7]Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky, Joshua B. Tenenbaum, Hugo Larochelle, Richard S. Zemel:
Meta-Learning for Semi-Supervised Few-Shot Classification. ICLR (Poster) 2018 - [c6]Yuhuai Wu, Mengye Ren, Renjie Liao, Roger B. Grosse:
Understanding Short-Horizon Bias in Stochastic Meta-Optimization. ICLR (Poster) 2018 - [c5]Mengye Ren, Wenyuan Zeng, Bin Yang, Raquel Urtasun:
Learning to Reweight Examples for Robust Deep Learning. ICML 2018: 4331-4340 - [i10]Mengye Ren, Andrei Pokrovsky, Bin Yang, Raquel Urtasun:
SBNet: Sparse Blocks Network for Fast Inference. CoRR abs/1801.02108 (2018) - [i9]Mengye Ren, Eleni Triantafillou, Sachin Ravi, Jake Snell, Kevin Swersky, Joshua B. Tenenbaum, Hugo Larochelle, Richard S. Zemel:
Meta-Learning for Semi-Supervised Few-Shot Classification. CoRR abs/1803.00676 (2018) - [i8]Yuhuai Wu, Mengye Ren, Renjie Liao, Roger B. Grosse:
Understanding Short-Horizon Bias in Stochastic Meta-Optimization. CoRR abs/1803.02021 (2018) - [i7]Mengye Ren, Wenyuan Zeng, Bin Yang, Raquel Urtasun:
Learning to Reweight Examples for Robust Deep Learning. CoRR abs/1803.09050 (2018) - [i6]Chris Zhang, Mengye Ren, Raquel Urtasun:
Graph HyperNetworks for Neural Architecture Search. CoRR abs/1810.05749 (2018) - [i5]Mengye Ren, Renjie Liao, Ethan Fetaya, Richard S. Zemel:
Incremental Few-Shot Learning with Attention Attractor Networks. CoRR abs/1810.07218 (2018) - 2017
- [c4]Mengye Ren, Richard S. Zemel:
End-to-End Instance Segmentation with Recurrent Attention. CVPR 2017: 293-301 - [c3]Mengye Ren, Renjie Liao, Raquel Urtasun, Fabian H. Sinz, Richard S. Zemel:
Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes. ICLR (Poster) 2017 - [c2]Aidan N. Gomez, Mengye Ren, Raquel Urtasun, Roger B. Grosse:
The Reversible Residual Network: Backpropagation Without Storing Activations. NIPS 2017: 2214-2224 - [i4]Aidan N. Gomez, Mengye Ren, Raquel Urtasun, Roger B. Grosse:
The Reversible Residual Network: Backpropagation Without Storing Activations. CoRR abs/1707.04585 (2017) - 2016
- [i3]Mengye Ren, Richard S. Zemel:
End-to-End Instance Segmentation and Counting with Recurrent Attention. CoRR abs/1605.09410 (2016) - [i2]Mengye Ren, Renjie Liao, Raquel Urtasun, Fabian H. Sinz, Richard S. Zemel:
Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes. CoRR abs/1611.04520 (2016) - 2015
- [c1]Mengye Ren, Ryan Kiros, Richard S. Zemel:
Exploring Models and Data for Image Question Answering. NIPS 2015: 2953-2961 - [i1]Mengye Ren, Ryan Kiros, Richard S. Zemel:
Image Question Answering: A Visual Semantic Embedding Model and a New Dataset. CoRR abs/1505.02074 (2015)
Coauthor Index
Raquel Urtasun
aka: Raquel Urtasun Waabi
aka: Raquel Urtasun Waabi
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last updated on 2024-09-26 01:51 CEST by the dblp team
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