Esophagus Silhouette Extraction and Reconstruction From Fluoroscopic Views for Cardiac Ablation Procedure Guidance. - Liron Yatziv; Julian Ibarz; Norbert Strobel; Saurabh Datta; Guillermo Sapiro (IEEE Trans. Inf. Technol. Biomed., 2011)

Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks. - Ian J. Goodfellow; Yaroslav Bulatov; Julian Ibarz; Sacha Arnoud; Vinay D. Shet (ICLR, 2014)

Large Scale Business Discovery from Street Level Imagery. - Qian Yu; Christian Szegedy; Martin C. Stumpe; Liron Yatziv; Vinay D. Shet; Julian Ibarz; Sacha Arnoud (CoRR, 2015)

End-to-End Interpretation of the French Street Name Signs Dataset. - Raymond Smith; Chunhui Gu; Dar-Shyang Lee; Huiyi Hu; Ranjith Unnikrishnan; Julian Ibarz; Sacha Arnoud; Sophia Lin (ECCV Workshops (1), 2016)

End-to-End Learning of Semantic Grasping. - Eric Jang; Sudheendra Vijayanarasimhan; Peter Pastor; Julian Ibarz; Sergey Levine (CoRL, 2017)

Attention-Based Extraction of Structured Information from Street View Imagery. - Zbigniew Wojna; Alexander N. Gorban; Dar-Shyang Lee; Kevin Murphy 002; Qian Yu; Yeqing Li; Julian Ibarz (ICDAR, 2017)

In-Datacenter Performance Analysis of a Tensor Processing Unit. - Norman P. Jouppi; Cliff Young; Nishant Patil; David A. Patterson 001; Gaurav Agrawal; Raminder Bajwa; Sarah Bates; Suresh Bhatia; Nan Boden; Al Borchers; Rick Boyle; Pierre-luc Cantin; et al. (ISCA, 2017)

In-Datacenter Performance Analysis of a Tensor Processing Unit. - Norman P. Jouppi; Cliff Young; Nishant Patil; David A. Patterson 001; Gaurav Agrawal; Raminder Bajwa; Sarah Bates; Suresh Bhatia; Nan Boden; Al Borchers; Rick Boyle; Pierre-luc Cantin; et al. (CoRR, 2017)

Discrete Sequential Prediction of Continuous Actions for Deep RL. - Luke Metz; Julian Ibarz; Navdeep Jaitly; James Davidson (CoRR, 2017)

Large Scale Scene Text Verification with Guided Attention. - Dafang He; Yeqing Li; Alexander N. Gorban; Derrall Heath; Julian Ibarz; Qian Yu; Daniel Kifer; C. Lee Giles (ACCV (5), 2018)

Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation. - Dmitry Kalashnikov; Alex Irpan; Peter Pastor; Julian Ibarz; Alexander Herzog; Eric Jang; Deirdre Quillen; Ethan Holly; Mrinal Kalakrishnan; Vincent Vanhoucke; Sergey Levine (CoRL, 2018)

Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning. - Benjamin Eysenbach; Shixiang Gu; Julian Ibarz; Sergey Levine (ICLR (Poster), 2018)

Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping. - Konstantinos Bousmalis; Alex Irpan; Paul Wohlhart; Yunfei Bai; Matthew Kelcey; Mrinal Kalakrishnan; Laura Downs; Julian Ibarz; Peter Pastor; Kurt Konolige; Sergey Levine; Vincent Vanhoucke (ICRA, 2018)

Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods. - Deirdre Quillen; Eric Jang; Ofir Nachum; Chelsea Finn; Julian Ibarz; Sergey Levine (ICRA, 2018)

Guided Attention for Large Scale Scene Text Verification. - Dafang He; Yeqing Li; Alexander N. Gorban; Derrall Heath; Julian Ibarz; Qian Yu; Daniel Kifer; C. Lee Giles (CoRR, 2018)

QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation. - Dmitry Kalashnikov; Alex Irpan; Peter Pastor; Julian Ibarz; Alexander Herzog; Eric Jang; Deirdre Quillen; Ethan Holly; Mrinal Kalakrishnan; Vincent Vanhoucke; Sergey Levine (CoRR, 2018)

Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection. - Sergey Levine; Peter Pastor; Alex Krizhevsky; Julian Ibarz; Deirdre Quillen (Int. J. Robotics Res., 2018)

Sim-To-Real via Sim-To-Sim: Data-Efficient Robotic Grasping via Randomized-To-Canonical Adaptation Networks. - Stephen James; Paul Wohlhart; Mrinal Kalakrishnan; Dmitry Kalashnikov; Alex Irpan; Julian Ibarz; Sergey Levine; Raia Hadsell; Konstantinos Bousmalis (CVPR, 2019)

Diversity is All You Need: Learning Skills without a Reward Function. - Benjamin Eysenbach; Abhishek Gupta 004; Julian Ibarz; Sergey Levine (ICLR (Poster), 2019)

Off-Policy Evaluation via Off-Policy Classification. - Alexander Irpan; Kanishka Rao; Konstantinos Bousmalis; Chris Harris 001; Julian Ibarz; Sergey Levine (NeurIPS, 2019)

RL-CycleGAN: Reinforcement Learning Aware Simulation-to-Real. - Kanishka Rao; Chris Harris 001; Alex Irpan; Sergey Levine; Julian Ibarz; Mohi Khansari (CVPR, 2020)

Thinking While Moving: Deep Reinforcement Learning with Concurrent Control. - Ted Xiao; Eric Jang; Dmitry Kalashnikov; Sergey Levine; Julian Ibarz; Karol Hausman; Alexander Herzog (ICLR, 2020)

Visionary: Vision architecture discovery for robot learning. - Iretiayo Akinola; Anelia Angelova; Yao Lu 006; Yevgen Chebotar; Dmitry Kalashnikov; Jacob Varley; Julian Ibarz; Michael S. Ryoo (ICRA, 2021)

How to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learned. - Julian Ibarz; Jie Tan 001; Chelsea Finn; Mrinal Kalakrishnan; Peter Pastor; Sergey Levine (CoRR, 2021)

MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance. - Michael Luo; Ashwin Balakrishna; Brijen Thananjeyan; Suraj Nair 003; Julian Ibarz; Jie Tan 001; Chelsea Finn; Ion Stoica; Ken Goldberg (CoRR, 2021)

How to train your robot with deep reinforcement learning: lessons we have learned. - Julian Ibarz; Jie Tan 001; Chelsea Finn; Mrinal Kalakrishnan; Peter Pastor; Sergey Levine (Int. J. Robotics Res., 2021)

Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones. - Brijen Thananjeyan; Ashwin Balakrishna; Suraj Nair 003; Michael Luo; Krishnan Srinivasan; Minho Hwang; Joseph E. Gonzalez; Julian Ibarz; Chelsea Finn; Ken Goldberg (IEEE Robotics Autom. Lett., 2021)

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. - Brian Ichter; Anthony Brohan; Yevgen Chebotar; Chelsea Finn; Karol Hausman; Alexander Herzog; Daniel Ho; Julian Ibarz; Alex Irpan; Eric Jang; Ryan Julian; Dmitry Kalashnikov; et al. (CoRL, 2022)

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances. - Michael Ahn; Anthony Brohan; Noah Brown; Yevgen Chebotar; Omar Cortes; Byron David; Chelsea Finn; Keerthana Gopalakrishnan; Karol Hausman; Alexander Herzog; Daniel Ho; Jasmine Hsu; et al. (CoRR, 2022)

Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions. - Yevgen Chebotar; Quan Vuong; Karol Hausman; Fei Xia 002; Yao Lu 006; Alex Irpan; Aviral Kumar; Tianhe Yu; Alexander Herzog; Karl Pertsch; Keerthana Gopalakrishnan; Julian Ibarz; et al. (CoRL, 2023)

Token Turing Machines. - Michael S. Ryoo; Keerthana Gopalakrishnan; Kumara Kahatapitiya; Ted Xiao; Kanishka Rao; Austin Stone; Yao Lu 006; Julian Ibarz; Anurag Arnab (CVPR, 2023)

RT-1: Robotics Transformer for Real-World Control at Scale. - Anthony Brohan; Noah Brown; Justice Carbajal; Yevgen Chebotar; Joseph Dabis; Chelsea Finn; Keerthana Gopalakrishnan; Karol Hausman; Alexander Herzog; Jasmine Hsu; Julian Ibarz; Brian Ichter; et al. (Robotics: Science and Systems, 2023)

Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. - Alexander Herzog; Kanishka Rao; Karol Hausman; Yao Lu 006; Paul Wohlhart; Mengyuan Yan; Jessica Lin; Montserrat Gonzalez Arenas; Ted Xiao; Daniel Kappler; Daniel Ho; Jarek Rettinghouse; et al. (Robotics: Science and Systems, 2023)

Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators. - Alexander Herzog; Kanishka Rao; Karol Hausman; Yao Lu 006; Paul Wohlhart; Mengyuan Yan; Jessica Lin; Montserrat Gonzalez Arenas; Ted Xiao; Daniel Kappler; Daniel Ho; Jarek Rettinghouse; et al. (CoRR, 2023)