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2024
Gaussian Process Regression-Based Near-Infrared d-Luciferin Analogue Design Using Mutation-Controlled Graph-Based Genetic Algorithm
Journal of Chemical Information and Modeling
2024
Machine Learning for Orbital Energies of Organic Molecules Upwards of 100 Atoms
physica status solidi (b)
2024
Comprehensive Computational Chemistry
2023
Generative Models as an Emerging Paradigm in the Chemical Sciences
Journal of the American Chemical Society
2023
Determining best practices for using genetic algorithms in molecular discovery
The Journal of Chemical Physics
2023
Genetic algorithm-based re-optimization of the Schrock catalyst for dinitrogen fixation
PeerJ Physical Chemistry
2023
Guided diffusion for inverse molecular design
Nature Computational Science
2023
AI‐Guided Design and Property Prediction for Zeolites and Nanoporous Materials
2022
Pareto Optimization of Oligomer Polarizability and Dipole Moment Using a Genetic Algorithm
The Journal of Physical Chemistry A
2022
A benchmark study of machine learning methods for molecular electronic transition: Tree‐based ensemble learning versus graph neural network
Bulletin of the Korean Chemical Society
2022
Graph-based molecular Pareto optimisation
Chemical Science
2022
Approaches for enhancing the analysis of chemical space for drug discovery
Expert Opinion on Drug Discovery
2022
Curiosity in exploring chemical spaces: intrinsic rewards for molecular reinforcement learning
Machine Learning: Science and Technology
2022
Towards a chemistry-informed paradigm for designing molecules
Current Opinion in Chemical Engineering
2022
Generating stable molecules using imitation and reinforcement learning
Machine Learning: Science and Technology
2022
Neural-network-backed evolutionary search for SrTiO3(110) surface reconstructions
Digital Discovery
2022
Using deep neural networks to explore chemical space
Expert Opinion on Drug Discovery
2022
Organic photoredox catalysts for CO2 reduction: Driving discovery with genetic algorithms
The Journal of Chemical Physics
2021
MOLGENGO: Finding Novel Molecules with Desired Electronic Properties by Capitalizing on Their Global Optimization
ACS Omega
2021
Deep molecular dreaming: inverse machine learning for de-novo molecular design and interpretability with surjective representations
Machine Learning: Science and Technology
2021
Defining and Exploring Chemical Spaces
Trends in Chemistry
2021
Beyond generative models: superfast traversal, optimization, novelty, exploration and discovery (STONED) algorithm for molecules using SELFIES
Chemical Science
2021
MolFinder: an evolutionary algorithm for the global optimization of molecular properties and the extensive exploration of chemical space using SMILES
Journal of Cheminformatics
2021
Perspective and challenges in electrochemical approaches for reactive CO2 separations
iScience
2020
Illuminating elite patches of chemical space
Chemical Science