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Diffusion models excel at modeling complex and multimodal trajectory distributions for decision-making and control.
ALVINN: an autonomous land vehicle in a neural network
Dean A. Pomerleau · 1989
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Optimization of computer simulation models with rare events
Reuven Y Rubinstein · 1997
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Generalized force model of traffic dynamics
Dirk Helbing and Benno Tilch · 1998
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The stanford entry in the urban challenge
M Montremerlo, J Beeker, S Bhat, and H Dahlkamp · 2008
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Trajectory planning for bertha—a local, continuous method
Julius Ziegler, Philipp Bender, Thao Dang, and Christoph Stiller · 2014
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Narain Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Model predictive path integral control using covariance variable importance sampling
Grady Williams, Andrew Aldrich, and Evangelos Theodorou · 2015
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End to end learning for self-driving cars, 2016
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D. Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, Xin Zhang, Jake Zhao, and Karol Zieba · 2016
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End-to-end driving via conditional imitation learning
Felipe Codevilla, Matthias Müller, Alexey Dosovitskiy, Antonio M. López, and Vladlen Koltun · 2017
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Motion prediction under multimodality with conditional stochastic networks, 2017
Katerina Fragkiadaki, Jonathan Huang, Alex Alemi, Sudheendra Vijayanarasimhan, Susanna Ricco, and Rahul Sukthankar · 2017
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Imitating driver behavior with generative adversarial networks
Alex Kuefler, Jeremy Morton, Tim Allan Wheeler, and Mykel John Kochenderfer · 2017
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The kinematic bicycle model: A consistent model for planning feasible trajectories for autonomous vehicles?
Philip Polack, Florent Altché, Brigitte d’Andréa Novel, and Arnaud de La Fortelle · 2017
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Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst
Mayank Bansal, Alex Krizhevsky, and Abhijit S. Ogale · 2018
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Baidu apollo em motion planner
Haoyang Fan, Fan Zhu, Changchun Liu, Liangliang Zhang, Li Zhuang, Dong Li, Weicheng Zhu, Jiangtao Hu, Hongye Li, and Qi Kong · 2018
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Dian Chen, Brady Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2019
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Yichuan Charlie Tang and Ruslan Salakhutdinov · 2019
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Danfei Xu, Roberto Martín-Martín, De-An Huang, Yuke Zhu, Silvio Savarese, and Li Fei-Fei · 2019
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End-to-end interpretable neural motion planner
Wenyuan Zeng, Wenjie Luo, Simon Suo, Abbas Sadat, Bin Yang, Sergio Casas, and Raquel Urtasun · 2019
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Language models are few-shot learners, 2020
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Hierarchical planning for long-horizon manipulation with geometric and symbolic scene graphs
Yifeng Zhu, Jonathan Tremblay, Stan Birchfield, and Yuke Zhu · 2020
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Lookout: Diverse multi-future prediction and planning for self-driving
Alexander Cui, Abbas Sadat, Sergio Casas, Renjie Liao, and Raquel Urtasun · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alex Nichol · 2021
Cited alongside, same era.
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig · 2021
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
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Multi-modal fusion transformer for end-to-end autonomous driving
Aditya Prakash, Kashyap Chitta, and Andreas Geiger · 2021
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Contingencies from observations: Tractable contingency planning with learned behavior models
Nicholas Rhinehart, Jeff He, Charles Packer, Matthew A Wright, Rowan McAllister, Joseph E Gonzalez, and Sergey Levine · 2021
Diffusion policy: Visuomotor policy learning via action diffusion, 2023
Cheng Chi, Siyuan Feng, Yilun Du, Zhenjia Xu, Eric Cousineau, Benjamin Burchfiel, and Shuran Song · 2023
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Parting with misconceptions about learning-based vehicle motion planning, 2023
Daniel Dauner, Marcel Hallgarten, Andreas Geiger, and Kashyap Chitta · 2023
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Energy-based Models are Zero-Shot Planners for Compositional Scene Rearrangement
Nikolaos Gkanatsios, Ayush Jain, Zhou Xian, Yunchu Zhang, Christopher Atkeson, and Katerina Fragkiadaki · 2023
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Visual programming: Compositional visual reasoning without training
Tanmay Gupta and Aniruddha Kembhavi · 2023
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Gaia-1: A generative world model for autonomous driving
Anthony Hu, Lloyd Russell, Hudson Yeo, Zak Murez, George Fedoseev, Alex Kendall, Jamie Shotton, and Gianluca Corrado · 2023
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Cited alongside, same era.
Urban driver: Learning to drive from real-world demonstrations using policy gradients
Oliver Scheel, Luca Bergamini, Maciej Wołczyk, Bla.zej Osi’nski, and Peter Ondruska · 2021
Cited alongside, same era.
Roformer: Enhanced transformer with rotary position embedding
Jianlin Su, Yu Lu, Shengfeng Pan, Ahmed Murtadha, Bo Wen, and Yunfeng Liu · 2021
Cited alongside, same era.
End-to-end urban driving by imitating a reinforcement learning coach
Zhejun Zhang, Alexander Liniger, Dengxin Dai, Fisher Yu, and Luc Van Gool · 2021
Cited alongside, same era.
Is conditional generative modeling all you need for decision-making?
Anurag Ajay, Yilun Du, Abhi Gupta, Joshua B. Tenenbaum, T. Jaakkola, and Pulkit Agrawal · 2022
Cited alongside, same era.
Nuplan: A closed-loop ml-based planning benchmark for autonomous vehicles, 2022
Holger Caesar, Juraj Kabzan, Kok Seang Tan, Whye Kit Fong, Eric Wolff, Alex Lang, Luke Fletcher, Oscar Beijbom, and Sammy Omari · 2022
Cited alongside, same era.
Learning from all vehicles, 2022
Dian Chen and Philipp Krähenbühl · 2022
Cited alongside, same era.
Planning with diffusion for flexible behavior synthesis
Michael Janner, Yilun Du, Joshua Tenenbaum, and Sergey Levine · 2022
Cited alongside, same era.
Voxposer: Composable 3d value maps for robotic manipulation with language models
Wenlong Huang, Chen Wang, Ruohan Zhang, Yunzhu Li, Jiajun Wu, and Li Fei-Fei · 2023
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Gen2sim: Scaling up robot learning in simulation with generative models, 2023
Pushkal Katara, Zhou Xian, and Katerina Fragkiadaki · 2023
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Dspy: Compiling declarative language model calls into self-improving pipelines
Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, Ashutosh Sharma, Thomas T. Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, and Christopher Potts · 2023
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Diverse multiple trajectory prediction using a two-stage prediction network trained with lane loss
Sanmin Kim, Hyeongseok Jeon, Jun Won Choi, and Dongsuk Kum · 2023
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Adaptdiffuser: Diffusion models as adaptive self-evolving planners
Zhixuan Liang, Yao Mu, Mingyu Ding, Fei Ni, Masayoshi Tomizuka, and Ping Luo · 2023
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Cheng Lu, Huayu Chen, Jianfei Chen, Hang Su, Chongxuan Li, and Jun Zhu · 2023
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Gpt-driver: Learning to drive with gpt
Jiageng Mao, Yuxi Qian, Hang Zhao, and Yue Wang · 2023
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Imitating human behaviour with diffusion models, 2023
Tim Pearce, Tabish Rashid, Anssi Kanervisto, Dave Bignell, Mingfei Sun, Raluca Georgescu, Sergio Valcarcel Macua, Shan Zheng Tan, Ida Momennejad, Katja Hofmann, and Sam Devlin · 2023
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Goal-conditioned imitation learning using score-based diffusion policies
Moritz Reuss, Maximilian Li, Xiaogang Jia, and Rudolf Lioutikov · 2023
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Motionlm: Multi-agent motion forecasting as language modeling
Ari Seff, Brian Cera, Dian Chen, Mason Ng, Aurick Zhou, Nigamaa Nayakanti, Khaled S Refaat, Rami Al-Rfou, and Benjamin Sapp · 2023
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Languagempc: Large language models as decision makers for autonomous driving
Hao Sha, Yao Mu, Yuxuan Jiang, Li Chen, Chenfeng Xu, Ping Luo, Shengbo Eben Li, Masayoshi Tomizuka, Wei Zhan, and Mingyu Ding · 2023
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Vipergpt: Visual inference via python execution for reasoning, 2023
Dídac Surís, Sachit Menon, and Carl Vondrick · 2023
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Se (3)-diffusionfields: Learning cost functions for joint grasp and motion optimization through diffusion
Julen Urain, Niklas Funk, Georgia Chalvatzaki, and Jan Peters · 2023
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On the road with gpt-4v (ision): Early explorations of visual-language model on autonomous driving
Licheng Wen, Xuemeng Yang, Daocheng Fu, Xiaofeng Wang, Pinlong Cai, Xin Li, Tao Ma, Yingxuan Li, Linran Xu, Dengke Shang, et al · 2023
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Chaineddiffuser: Unifying trajectory diffusion and keypose prediction for robotic manipulation
Zhou Xian, Nikolaos Gkanatsios, Théophile Gervet, Tsung-Wei Ke, and Katerina Fragkiadaki · 2023
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Drivegpt4: Interpretable end-to-end autonomous driving via large language model
Zhenhua Xu, Yujia Zhang, Enze Xie, Zhen Zhao, Yong Guo, Kenneth KY Wong, Zhenguo Li, and Hengshuang Zhao · 2023
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Learning interactive real-world simulators
Mengjiao Yang, Yilun Du, Kamyar Ghasemipour, Jonathan Tompson, Dale Schuurmans, and Pieter Abbeel · 2023
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Language to rewards for robotic skill synthesis
Wenhao Yu, Nimrod Gileadi, Chuyuan Fu, Sean Kirmani, Kuang-Huei Lee, Montse Gonzalez Arenas, Hao-Tien Lewis Chiang, Tom Erez, Leonard Hasenclever, Jan Humplik, et al · 2023
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