{"total":38,"rows":[{"id":"2202.07141","title":"Machine Learning in Aerodynamic Shape Optimization","created":"2022-02-15","cited_by_count":39,"area":null},{"id":"2304.02370","title":"Effective control of two-dimensional Rayleigh--B\\'enard convection: invariant multi-agent reinforcement learning is all you need","created":"2023-04-05","cited_by_count":27,"area":null},{"id":"2108.00128","title":"Physics-informed Dyna-Style Model-Based Deep Reinforcement Learning for Dynamic Control","created":"2021-07-31","cited_by_count":23,"area":null},{"id":"2309.15421","title":"Deep Learning in Deterministic Computational Mechanics","created":"2023-09-27","cited_by_count":21,"area":null},{"id":"2208.14226","title":"Unsupervised Representation Learning in Deep Reinforcement Learning: A Review","created":"2022-08-27","cited_by_count":18,"area":null},{"id":"2303.07647","title":"Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review","created":"2023-03-14","cited_by_count":15,"area":null},{"id":"2310.05227","title":"Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology","created":"2023-10-08","cited_by_count":11,"area":null},{"id":"2202.11170","title":"Multi-fidelity reinforcement learning framework for shape optimization","created":"2022-02-22","cited_by_count":9,"area":null},{"id":"2203.05775","title":"A Thermodynamics-informed Active Learning Approach to Perception and Reasoning about Fluids","created":"2022-03-11","cited_by_count":9,"area":null},{"id":"2312.05583","title":"Better Neural PDE Solvers Through Data-Free Mesh Movers","created":"2023-12-09","cited_by_count":9,"area":null},{"id":"2407.21565","title":"Multi-agent reinforcement learning for the control of three-dimensional Rayleigh-B\\'enard convection","created":"2024-07-31","cited_by_count":8,"area":null},{"id":"2307.01995","title":"Dynamic Feature-based Deep Reinforcement Learning for Flow Control of Circular Cylinder with Sparse Surface Pressure Sensing","created":"2023-07-05","cited_by_count":7,"area":null},{"id":"2110.05945","title":"Multi-condition multi-objective optimization using deep reinforcement learning","created":"2021-10-10","cited_by_count":6,"area":null},{"id":"2202.11664","title":"Comparative analysis of machine learning methods for active flow control","created":"2022-02-23","cited_by_count":6,"area":null},{"id":"2302.07160","title":"Learning a model is paramount for sample efficiency in reinforcement learning control of PDEs","created":"2023-02-14","cited_by_count":6,"area":null},{"id":"2301.12098","title":"Turbulence control in plane Couette flow using low-dimensional neural ODE-based models and deep reinforcement learning","created":"2023-01-28","cited_by_count":5,"area":null},{"id":"2304.11526","title":"How to Control Hydrodynamic Force on Fluidic Pinball via Deep Reinforcement Learning","created":"2023-04-23","cited_by_count":5,"area":null},{"id":"2407.17822","title":"Advanced deep-reinforcement-learning methods for flow control: group-invariant and positional-encoding networks improve learning speed and quality","created":"2024-07-25","cited_by_count":5,"area":null},{"id":"2306.08292","title":"A reinforcement learning strategy for p-adaptation in high order solvers","created":"2023-06-14","cited_by_count":4,"area":null},{"id":"2409.05709","title":"Real-time optimal control of high-dimensional parametrized systems by deep learning-based reduced order models","created":"2024-09-09","cited_by_count":4,"area":null},{"id":"2212.12207","title":"Investigation of reinforcement learning for shape optimization of profile extrusion dies","created":"2022-12-23","cited_by_count":2,"area":null},{"id":"2304.12330","title":"Parallel bootstrap-based on-policy deep reinforcement learning for continuous flow control applications","created":"2023-04-24","cited_by_count":2,"area":null},{"id":"2307.05735","title":"Effective Latent Differential Equation Models via Attention and Multiple Shooting","created":"2023-07-11","cited_by_count":2,"area":null},{"id":"2504.14422","title":"Optimal Lattice Boltzmann Closures through Multi-Agent Reinforcement Learning","created":"2025-04-19","cited_by_count":2,"area":null},{"id":"2107.03015","title":"Evaluating the progress of Deep Reinforcement Learning in the real world: aligning domain-agnostic and domain-specific research","created":"2021-07-07","cited_by_count":1,"area":null},{"id":"2204.04292","title":"Evolving Pareto-Optimal Actor-Critic Algorithms for Generalizability and Stability","created":"2022-04-08","cited_by_count":1,"area":null},{"id":"2212.01428","title":"MeshDQN: A Deep Reinforcement Learning Framework for Improving Meshes in Computational Fluid Dynamics","created":"2022-12-02","cited_by_count":1,"area":null},{"id":"2403.01005","title":"Policy Optimization for PDE Control with a Warm Start","created":"2024-03-01","cited_by_count":1,"area":null},{"id":"2410.15250","title":"Multi-modal Policies with Physics-informed Representations in Complex Fluid Environments","created":"2024-10-20","cited_by_count":1,"area":null},{"id":"2503.08410","title":"A Deep-Learning Iterative Stacked Approach for Prediction of Reactive Dissolution in Porous Media","created":"2025-03-11","cited_by_count":1,"area":null},{"id":"2201.00732","title":"Classifying Turbulent Environments via Machine Learning","created":"2022-01-03","cited_by_count":0,"area":null},{"id":"2204.03840","title":"Data-Driven Evaluation of Training Action Space for Reinforcement Learning","created":"2022-04-08","cited_by_count":0,"area":null},{"id":"2207.12854","title":"Variational multiscale reinforcement learning for discovering reduced order closure models of nonlinear spatiotemporal transport systems","created":"2022-07-07","cited_by_count":0,"area":null},{"id":"2308.00086","title":"An unsupervised machine-learning-based shock sensor for high-order supersonic flow solvers","created":"2023-07-28","cited_by_count":0,"area":null},{"id":"2309.06869","title":"Dynamic control of self-assembly of quasicrystalline structures through reinforcement learning","created":"2023-09-13","cited_by_count":0,"area":null},{"id":"2412.09942","title":"Latent feedback control of distributed systems in multiple scenarios through deep learning-based reduced order models","created":"2024-12-13","cited_by_count":0,"area":null},{"id":"2507.04309","title":"Domain Adaptation of Drag Reduction Policy to Partial Measurements","created":"2025-07-06","cited_by_count":0,"area":null},{"id":"2510.07106","title":"Active Control of Turbulent Airfoil Flows Using Adjoint-based Deep Learning","created":"2025-10-08","cited_by_count":0,"area":null}],"next_cursor":null}