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ORCIDBrandon Trabucco
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2020 – today
- 2024
[c7]Brandon Trabucco, Kyle Doherty, Max Gurinas, Ruslan Salakhutdinov:
Effective Data Augmentation With Diffusion Models. ICLR 2024- [i11]Michael Luo, Justin Wong, Brandon Trabucco, Yanping Huang, Joseph E. Gonzalez, Zhifeng Chen, Ruslan Salakhutdinov, Ion Stoica:
Stylus: Automatic Adapter Selection for Diffusion Models. CoRR abs/2404.18928 (2024) - [i10]Kyle Doherty, Max Gurinas, Erik Samsoe, Charles Casper, Beau Larkin, Philip Ramsey, Brandon Trabucco, Ruslan Salakhutdinov:
Leafy Spurge Dataset: Real-world Weed Classification Within Aerial Drone Imagery. CoRR abs/2405.03702 (2024) - [i9]Brandon Trabucco, Max Gurinas, Kyle Doherty, Ruslan Salakhutdinov:
Understanding Visual Concepts Across Models. CoRR abs/2406.07506 (2024) - 2023
- [c6]Brandon Trabucco, Gunnar A. Sigurdsson, Robinson Piramuthu, Gaurav S. Sukhatme, Ruslan Salakhutdinov:
A Simple Approach for Visual Room Rearrangement: 3D Mapping and Semantic Search. ICLR 2023 - [i8]Brandon Trabucco, Kyle Doherty, Max Gurinas, Ruslan Salakhutdinov:
Effective Data Augmentation With Diffusion Models. CoRR abs/2302.07944 (2023) - 2022
- [c5]Brandon Trabucco, Xinyang Geng, Aviral Kumar, Sergey Levine:
Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization. ICML 2022: 21658-21676 - [c4]Brandon Trabucco, Mariano Phielipp, Glen Berseth:
AnyMorph: Learning Transferable Polices By Inferring Agent Morphology. ICML 2022: 21677-21691 - [i7]Brandon Trabucco, Xinyang Geng, Aviral Kumar, Sergey Levine:
Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization. CoRR abs/2202.08450 (2022) - [i6]Brandon Trabucco, Mariano Phielipp, Glen Berseth:
AnyMorph: Learning Transferable Polices By Inferring Agent Morphology. CoRR abs/2206.12279 (2022) - [i5]Brandon Trabucco, Gunnar A. Sigurdsson, Robinson Piramuthu, Gaurav S. Sukhatme, Ruslan Salakhutdinov:
A Simple Approach for Visual Rearrangement: 3D Mapping and Semantic Search. CoRR abs/2206.13396 (2022) - 2021
- [c3]Xuanlin Li, Brandon Trabucco, Dong Huk Park, Michael Luo, Sheng Shen, Trevor Darrell, Yang Gao:
Discovering Non-monotonic Autoregressive Orderings with Variational Inference. ICLR 2021 - [c2]Brandon Trabucco, Aviral Kumar, Xinyang Geng, Sergey Levine:
Conservative Objective Models for Effective Offline Model-Based Optimization. ICML 2021: 10358-10368 - [i4]Brandon Trabucco, Aviral Kumar, Xinyang Geng, Sergey Levine:
Conservative Objective Models for Effective Offline Model-Based Optimization. CoRR abs/2107.06882 (2021) - [i3]Xuanlin Li, Brandon Trabucco, Dong Huk Park, Michael Luo, Sheng Shen, Trevor Darrell, Yang Gao:
Discovering Non-monotonic Autoregressive Orderings with Variational Inference. CoRR abs/2110.15797 (2021)
2010 – 2019
- 2019
- [c1]Richard Shin, Neel Kant, Kavi Gupta, Chris Bender, Brandon Trabucco, Rishabh Singh, Dawn Song:
Synthetic Datasets for Neural Program Synthesis. ICLR (Poster) 2019 - [i2]Brandon Trabucco, Albert Qu, Simon Li, Ganeshkumar Ashokavardhanan:
Inferring the Optimal Policy using Markov Chain Monte Carlo. CoRR abs/1912.02714 (2019) - [i1]Richard Shin, Neel Kant, Kavi Gupta, Christopher Bender, Brandon Trabucco, Rishabh Singh, Dawn Song:
Synthetic Datasets for Neural Program Synthesis. CoRR abs/1912.12345 (2019)
Coauthor Index
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