Awesome-Offline-Model-based-Optimization

📰 Must-read papers on Offline Model-based Optimization 🔥

🔍 Table of Contents

• 🌟 What is Offline Model-based Optimization?
• 🔗 Benchmarks
• 🎯 Surrogate Models-based Methods
• 🤔 Generative Models-based Methods
• 📍 Other Applications
• 🤗 Contribution
  • Contributors
  • Acknowledgement

🌟 What is Offline Model-based Optimization?

🔗 Benchmarks

• Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization ICML 2022 Jul

• BayesO Benchmarks: Benchmark Functions for Bayesian Optimization Zenodo 2023 Jan

🎯 Surrogate Models-based Methods

• Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation ICLR 2021 Feb

• Conservative Objective Models for Effective Offline Model-Based Optimization ICML 2021 Jul

• RoMA: Robust Model Adaptation for Offline Model-based Optimization NeurIPS 2021 Oct

• Bidirectional Learning for Offline Infinite-width Model-based Optimization NeurIPS 2022 Sep

• Data-Driven Offline Decision-Making via Invariant Representation Learning NeurIPS 2022 Nov

• Conflict-Averse Gradient Optimization of Ensembles for Effective Offline Model-Based Optimization Arxiv 2023 Mar

• Degradation-Resistant Offline Optimization via Accumulative Risk Control ECAI 2023 Apr

• Importance-aware Co-teaching for Offline Model-based Optimization NeurIPS 2023 Sep

• Parallel-mentoring for Offline Model-based Optimization NeurIPS 2023 Sep

• SENSITIVITY-INFORMED REGULARIZATION FOR OFFLINE BLACK-BOX OPTIMIZATION Openreview 2023 Sep

• ROMO: Retrieval-enhanced Offline Model-based Optimization DAI 2023 Dec

• Learning Surrogates for Offline Black-Box Optimization via Gradient Matching ICML 2024 May

🤔 Generative Models-based Methods

• Conditioning by adaptive sampling for robust design ICML 2019 Jul

• Model Inversion Networks for Model-Based Optimization NeurIPS 2019 Dec

• Autofocused oracles for model-based design NeurIPS 2020 Jun

• Generative Pretraining for Black-Box Optimization ICML 2022 Jun

• Conservative objective models are a special kind of contrastive divergence-based energy model Arxiv 2023 Apr

• Diffusion Models for Black-Box Optimization ICML 2023 Jun

• From Function to Distribution Modeling: A PAC-Generative Approach to Offline Optimization Arxiv 2024 Jan

• Generative Adversarial Bayesian Optimization for Surrogate Objectives Arxiv 2024 Feb

• Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints Arxiv 2024 Feb

• Diffusion Model for Data-Driven Black-Box Optimization Arxiv 2024 Mar

• Offline Model-Based Optimization via Policy-Guided Gradient Search AAAI 2024 May

• Design Editing for Offline Model-based Optimization Arxiv 2024 May

📍 Other Applications

🧬 Bio Sequences Design

• Bidirectional Learning for Offline Model-based Biological Sequence Design ICML 2023 Jan

• Importance Weighted Expectation-Maximization for Protein Sequence Design ICML 2023 Apr

• Plug & play directed evolution of proteins with gradient-based discrete MCMC IOP Science 2023 Apr

• Conservative objective models for biological sequence design Technical Report 2023 May

• Bootstrapped Training of Score-Conditioned Generator for Offline Design of Biological Sequences NeurIPS 2023 Jun

• High-Dimensional Dueling Optimization with Preference AAAI 2023 Jun

• Improving protein optimization with smoothed fitness landscapes ICLR 2024 Jan

• Fine-Tuning of Continuous-Time Diffusion Models as Entropy-Regularized Control Arxiv 2024 Feb

• Dual-Space Optimization: Improved Molecule Sequence Design by Latent Prompt Transformer Arxiv 2024 Feb

• Antibody Design with Constrained Bayesian Optimization ICLR GEM Workshop 2024 Mar

• Designing Biological Sequences without Prior Knowledge Using Evolutionary Reinforcement Learning AAAI 2024 Mar

• Latent-based Directed Evolution accelerated by Gradient Ascent for Protein Sequence Design BioArxiv 2024 Apr

🛫 Fluid Design

• Inverse Design for Fluid-Structure Interactions using Graph Network Simulators NeurIPS 2022 Nov

🌊 GFlowNet

• Biological Sequence Design with GFlowNets ICML 2022 Mar

• Learning GFlowNets from partial episodes for improved convergence and stability ICML 2022 Sep

• Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions Arxiv 2022 Nov

• Stochastic Generative Flow Networks UAI 2023 Feb

• Learning to Scale Logits for Temperature-Conditional GFlowNets NeurIPS AI4Science Workshop 2023 Oct

• Generative Flow Networks Assisted Biological Sequence Editing NeurIPS GenBio Workshop 2023 Oct

• Learning Energy Decompositions for Partial Inference in GFlowNets ICLR 2024 Jan

• Dynamic Backtracking in GFlowNets: Enhancing Decision Steps with Reward-Dependent Adjustment Mechanisms Arxiv 2024 Apr

🎯 Few Shot

• Evoopt: an msa-guided, fully unsupervised sequence optimization pipeline for protein design NeurIPS ML4Structural Bio Workshop 2022 Dec

• ExPT: Synthetic Pretraining for Few-Shot Experimental Design NeurIPS 2023 Oct

🌃 Graph Models

• Functional Graphical Models: Structure Enables Offline Data-Driven Optimization AISTATS 2024 May

🧐 Distribution Shift Detection

• Beyond the training set: an intuitive method for detecting distribution shift in model-based optimization Arxiv 2023 Nov

💻 Online Optimization

• Feedback Efficient Online Fine-Tuning of Diffusion Models Arxiv 2024 Feb

📈 LM Regressor

• OmniPred: Language Models as Universal Regressors Arxiv 2024 Feb

📑 Active Learning

• Deep Active Learning for Scientific Computing in the Wild Arxiv 2023 Jan

⌚️ Metrics

• Exploring validation metrics for offline model-based optimisation with diffusion models Arxiv 2022 Nov

🧑‍🏫 Position Paper

• Position: Leverage foundational models for black-box optimization Arxiv 2024 May

🧮 Dynamic Computation

• A Data Stream Ensemble Assisted Multifactorial Evolutionary Algorithm for Offline Data-Driven Dynamic Optimization Evolutionary Computation 2023 Dec

🧠 EEG/ECoG BCI

• Enhancing DNN Models for EEG/ECoG BCI With a Novel Data-Driven Offline Optimization Method IEEE Access 2023 Apr

🧪 Other

• Virtual laboratories: Transforming research with ai Techrxiv 2023 Jan

🎓 PhD Theses

• Learning to Optimize: Applications in Physical Designs and Manufacturing UNIVERSITY OF MICHIGAN LIBRARY 2022 Jan

• Offline Data-Driven Optimization: Benchmarks, Algorithms and Applications University of California, Berkeley ProQuest Dissertations & Theses 2023 Jan

• Deep Learning for the modeling and design of artificial electromagnetic materials Duke University ProQuest Dissertations & Theses 2023 Jan

🃏 Game Card Deck Building

• Deep surrogate assisted MAP-elites for automated hearthstone deckbuilding GECCO 2022 Jul

⚙️ Hardware Optimization

• Data-Driven Offline Optimization For Architecting Hardware Accelerators Arxiv 2021 Oct

💎 Crystal Structure Prediction

• Latent Conservative Objective Models for Data-Driven Crystal Structure Prediction Arxiv 2023 Oct

🏭 Industrial Control

• A cGAN Ensemble-based Uncertainty-aware Surrogate Model for Offline Model-based Optimization in Industrial Control Problems IJCNN 2022 May

🤗 Contribution

Contributors

Ye Yuan

Contributing to this project

Please feel free to file a PR for contributing to this project! Thanks so much for your help!

Acknowledgement