Fetching the paper…
Reading the bibliography…
Offline model-based optimization (MBO) aims to maximize a black-box objective function using only an offline dataset of designs and scores.
Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams · 1992
Earlier work this paper cites.
The CMA evolution strategy: A comparing review
Nikolaus Hansen · 2006
Earlier work this paper cites.
A connection between score matching and denoising autoencoders
Pascal Vincent · 2011
Earlier work this paper cites.
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, and Ruslan R. Salakhutdinov · 2012
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
Survey of variation in human transcription factors reveals prevalent dna binding changes
Luis A Barrera et al · 2016
Earlier work this paper cites.
Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
Earlier work this paper cites.
Local fitness landscape of the green fluorescent protein
Karen S Sarkisyan et al · 2016
Earlier work this paper cites.
The reparameterization trick for acquisition functions
James T Wilson, Riccardo Moriconi, Frank Hutter, and Marc Peter Deisenroth · 2017
Earlier work this paper cites.
Neural architecture search with reinforcement learning
Barret Zoph and Quoc V. Le · 2017
Earlier work this paper cites.
A data-driven statistical model for predicting the critical temperature of a superconductor
Kam Hamidieh · 2018
Earlier work this paper cites.
Conditioning by adaptive sampling for robust design
David H. Brookes, Hahnbeom Park, and Jennifer Listgarten · 2019
Earlier work this paper cites.
Data-efficient learning of morphology and controller for a microrobot
Thomas Liao, Grant Wang, Brian Yang, Rene Lee, Kristofer Pister, Sergey Levine, and Roberto Calandra · 2019
Earlier work this paper cites.
Human 5 UTR design and variant effect prediction from a massively parallel translation assay
Paul J Sample, Ban Wang, David W Reid, Vlad Presnyak, Iain J McFadyen, David R Morris, and Georg Seelig · 2019
Earlier work this paper cites.
Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
Earlier work this paper cites.
Robel: Robotics benchmarks for learning with low-cost robots
Michael Ahn, Henry Zhu, Kristian Hartikainen, Hugo Ponte, Abhishek Gupta, Sergey Levine, and Vikash Kumar · 2020
Earlier work this paper cites.
Model-based reinforcement learning for biological sequence design
Christof Angermüller, David Dohan, David Belanger, Ramya Deshpande, Kevin Murphy, and Lucy Colwell · 2020
Earlier work this paper cites.
Autofocused oracles for model-based design
Clara Fannjiang and Jennifer Listgarten · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Earlier work this paper cites.
Model inversion networks for model-based optimization
Aviral Kumar and Sergey Levine · 2020
Earlier work this paper cites.
Offline model-based optimization via normalized maximum likelihood estimation
Justin Fu and Sergey Levine · 2021
Cited alongside, same era.
A variational perspective on diffusion-based generative models and score matching
Chin-Wei Huang, Jae Hyun Lim, and Aaron C. Courville · 2021
Cited alongside, same era.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
Cited alongside, same era.
Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2021
Cited alongside, same era.
Conservative objective models for effective offline model-based optimization
Brandon Trabucco, Aviral Kumar, Xinyang Geng, and Sergey Levine · 2021
Cited alongside, same era.
Roma: Robust model adaptation for offline model-based optimization
Null-text inversion for editing real images using guided diffusion models
Ron Mokady, Amir Hertz, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or · 2023
Later among the works it cites.
Expt: Synthetic pretraining for few-shot experimental design
Tung Nguyen, Sudhanshu Agrawal, and Aditya Grover · 2023
Later among the works it cites.
Fatezero: Fusing attentions for zero-shot text-based video editing
Chenyang Qi, Xiaodong Cun, Yong Zhang, Chenyang Lei, Xintao Wang, Ying Shan, and Qifeng Chen · 2023
Later among the works it cites.
Dual diffusion implicit bridges for image-to-image translation
Xuan Su, Jiaming Song, Chenlin Meng, and Stefano Ermon · 2023
Later among the works it cites.
A latent space of stochastic diffusion models for zero-shot image editing and guidance
Chen Henry Wu and Fernando De la Torre · 2023
Later among the works it cites.
Rerender a video: Zero-shot text-guided video-to-video translation
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Sihyun Yu, Sungsoo Ahn, Le Song, and Jinwoo Shin · 2021
Cited alongside, same era.
Bidirectional learning for offline infinite-width model-based optimization
Can Chen, Yingxue Zhang, Jie Fu, Xue (Steve) Liu, and Mark Coates · 2022
Cited alongside, same era.
Classifier-free diffusion guidance, 2022
Jonathan Ho and Tim Salimans · 2022
Cited alongside, same era.
Sdedit: Guided image synthesis and editing with stochastic differential equations
Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon · 2022
Cited alongside, same era.
Data-driven offline decision-making via invariant representation learning
Han Qi, Yi Su, Aviral Kumar, and Sergey Levine · 2022
Cited alongside, same era.
Design-bench: Benchmarks for data-driven offline model-based optimization
Brandon Trabucco, Xinyang Geng, Aviral Kumar, and Sergey Levine · 2022
Cited alongside, same era.
Pix2video: Video editing using image diffusion
Duygu Ceylan, Chun-Hao Paul Huang, and Niloy J. Mitra · 2023
Cited alongside, same era.
Shuai Yang, Yifan Zhou, Ziwei Liu, and Chen Change Loy · 2023
Later among the works it cites.
Importance-aware co-teaching for offline model-based optimization
Ye Yuan, Can Chen, Zixuan Liu, Willie Neiswanger, and Xue (Steve) Liu · 2023
Later among the works it cites.
Offline model-based optimization via policy-guided gradient search
Yassine Chemingui, Aryan Deshwal, Trong Nghia Hoang, and Janardhan Rao Doppa · 2024
Closest in time.
Robust guided diffusion for offline black-box optimization
Can Chen, Christopher Beckham, Zixuan Liu, Xue Liu, and Christopher Pal · 2024
Closest in time.
FLATTEN: optical flow-guided attention for consistent text-to-video editing
Yuren Cong, Mengmeng Xu, Christian Simon, Shoufa Chen, Jiawei Ren, Yanping Xie, Juan-Manuel Pérez-Rúa, Bodo Rosenhahn, Tao Xiang, and Sen He · 2024
Closest in time.
Incorporating surrogate gradient norm to improve offline optimization techniques
Cuong Dao, Phi Le Nguyen, Truong Thao Nguyen, and Nghia Hoang · 2024
Closest in time.
Boosting offline optimizers with surrogate sensitivity
Manh Cuong Dao, Phi Le Nguyen, Truong Thao Nguyen, and Trong Nghia Hoang · 2024
Closest in time.
Tokenflow: Consistent diffusion features for consistent video editing
Michal Geyer, Omer Bar-Tal, Shai Bagon, and Tali Dekel · 2024
Closest in time.
Learning surrogates for offline black-box optimization via gradient matching
Minh Hoang, Azza Fadhel, Aryan Deshwal, Jana Doppa, and Trong Nghia Hoang · 2024
Closest in time.
Generative adversarial model-based optimization via source critic regularization
Michael S. Yao, Yimeng Zeng, Hamsa Bastani, Jacob R. Gardner, James C. Gee, and Osbert Bastani · 2024
Closest in time.
Paretoflow: Guided flows in multi-objective optimization, 2024
Ye Yuan, Can Chen, Christopher Pal, and Xue Liu · 2024
Closest in time.
Fastvideoedit: Leveraging consistency models for efficient text-to-video editing
Youyuan Zhang, Xuan Ju, and James J Clark · 2024
Closest in time.
Affinityflow: Guided flows for antibody affinity maturation
Can Chen, Karla-Luise Herpoldt, Chenchao Zhao, Zichen Wang, Marcus Collins, Shang Shang, and Ron Benson · 2025
Closest in time.
From Low To High-value Designs: Offline Optimization Via Generalized Diffusion, 2025
Manh Cuong Dao, The Hung Tran, Phi Le Nguyen, Thao Nguyen Truong, and Trong Nghia Hoang · 2025
Closest in time.
Offline model-based optimization: Comprehensive review
Minsu Kim, Jiayao Gu, Ye Yuan, Taeyoung Yun, Zixuan Liu, Yoshua Bengio, and Can Chen · 2025
Closest in time.