Byron David

According to our database, Byron David authored at least 6 papers between 2021 and 2024.

Collaborative distances:

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

2024

VADER: Visual Affordance Detection and Error Recovery for Multi Robot Human Collaboration.

Michael Ahn, Montserrat Gonzalez Arenas, Matthew Bennice, Noah Brown, Christine Chan, Byron David, Anthony G. Francis, Gavin Gonzalez, Rainer Hessmer, Tomas Jackson, Nikhil J. Joshi, Daniel Lam, Tsang-Wei Edward Lee, Alex Luong, Sharath Maddineni, Harsh Patel, Jodilyn Peralta, Jornell Quiambao, Diego Reyes, Rosario Jauregui Ruano, Dorsa Sadigh, Pannag Sanketi, Leila Takayama, Pavel Vodenski, Fei Xia

CoRR, 2024

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, Julian Ibarz, Brian Ichter, Alex Irpan, Eric Jang, Rosario Jauregui Ruano, Kyle Jeffrey, Sally Jesmonth, Nikhil J. Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Kuang-Huei Lee, Sergey Levine, Yao Lu, Linda Luu, Carolina Parada, Peter Pastor, Jornell Quiambao, Kanishka Rao, Jarek Rettinghouse, Diego Reyes, Pierre Sermanet, Nicolas Sievers, Clayton Tan, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Mengyuan Yan

CoRR, 2022

From Message to Expression: Exploring Non-Verbal Communication for Appearance-Constrained Robots.

Elaheh Sanoubari, Byron David, J. Chase Kew, Corbin Cunningham, Ken Caluwaerts

Proceedings of the 31st IEEE International Conference on Robot and Human Interactive Communication, 2022

Blocks Assemble! Learning to Assemble with Large-Scale Structured Reinforcement Learning.

Seyed Kamyar Seyed Ghasemipour, Satoshi Kataoka, Byron David, Daniel Freeman, Shixiang Shane Gu, Igor Mordatch

Proceedings of the International Conference on Machine Learning, 2022

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, Sergey Levine, Yao Lu, Carolina Parada, Kanishka Rao, Pierre Sermanet, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Mengyuan Yan, Noah Brown, Michael Ahn, Omar Cortes, Nicolas Sievers, Clayton Tan, Sichun Xu, Diego Reyes, Jarek Rettinghouse, Jornell Quiambao, Peter Pastor, Linda Luu, Kuang-Huei Lee, Yuheng Kuang, Sally Jesmonth, Nikhil J. Joshi, Kyle Jeffrey, Rosario Jauregui Ruano, Jasmine Hsu, Keerthana Gopalakrishnan, Byron David, Andy Zeng, Chuyuan Kelly Fu

Proceedings of the Conference on Robot Learning, 2022

2021

Braxlines: Fast and Interactive Toolkit for RL-driven Behavior Engineering beyond Reward Maximization.

Shixiang Shane Gu, Manfred Diaz, C. Daniel Freeman, Hiroki Furuta, Seyed Kamyar Seyed Ghasemipour, Anton Raichuk, Byron David, Erik Frey, Erwin Coumans, Olivier Bachem

CoRR, 2021