49 citations · 55 across the 7 of their papers we have counts for
7 papers
Uncertainty separation via ensemble quantile regression
Navid Ansari, Hans-Peter Seidel, Vahid Babaei
This paper introduces a novel and scalable framework for uncertainty estimation and separation with applications in data driven modeling in science and engineering tasks where reli…
Two-Stage Pretraining for Molecular Property Prediction in the Wild
Kevin Tirta Wijaya, Minghao Guo, Michael Sun +3
Molecular deep learning models have achieved remarkable success in property prediction, but they often require large amounts of labeled data. The challenge is that, in real-world a…
TrustMol: Trustworthy Inverse Molecular Design via Alignment with Molecular Dynamics
Kevin Tirta Wijaya, Navid Ansari, Hans-Peter Seidel +1
Data-driven generation of molecules with desired properties, also known as inverse molecular design (IMD), has attracted significant attention in recent years. Despite the signific…
Large-Batch, Iteration-Efficient Neural Bayesian Design Optimization
Navid Ansari, Alireza Javanmardi, Eyke Hüllermeier +2
Bayesian optimization (BO) provides a powerful framework for optimizing black-box, expensive-to-evaluate functions. It is therefore an attractive tool for engineering design proble…
Autoinverse: Uncertainty Aware Inversion of Neural Networks
Navid Ansari, Hans-Peter Seidel, Nima Vahidi Ferdowsi +1
Neural networks are powerful surrogates for numerous forward processes. The inversion of such surrogates is extremely valuable in science and engineering. The most important proper…
Closed-Loop Control of Direct Ink Writing via Reinforcement Learning
Michal Piovarci, Michael Foshey, Jie Xu +6
Enabling additive manufacturing to employ a wide range of novel, functional materials can be a major boost to this technology. However, making such materials printable requires pai…
Mixed Integer Neural Inverse Design
Navid Ansari, Hans-Peter Seidel, Vahid Babaei
In computational design and fabrication, neural networks are becoming important surrogates for bulky forward simulations. A long-standing, intertwined question is that of inverse d…