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Found 5 papers, 3 papers with code
TrustMol: Trustworthy Inverse Molecular Design via Alignment with Molecular Dynamics
Moreover, we propose a latent-property pairs acquisition method to effectively navigate the complexities of molecular latent optimization, a process that seems intuitive yet challenging due to the high-frequency and discontinuous nature of molecule space.
Large-Batch, Iteration-Efficient Neural Bayesian Design Optimization
Bayesian optimization (BO) provides a powerful framework for optimizing black-box, expensive-to-evaluate functions.
Autoinverse: Uncertainty Aware Inversion of Neural Networks
Neural networks are powerful surrogates for numerous forward processes.
Closed-Loop Control of Additive Manufacturing via Reinforcement Learning
We further show that in combination with reinforcement learning, our model can be used to discover control policies that outperform state-of-the-art controllers.
Mixed Integer Neural Inverse Design
Our mixed-integer inverse design uncovers globally optimal or near optimal solutions in a principled manner.
