Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 7 of 7 for “"reaction prediction"”.
-
Algorithmic Approaches for Context-Informed Reaction Prediction
… an ecosystem of tools for understanding chemical reactions is under development with the ultimate aim of accelerating lab-based workflows. This thesis makes contributions across this ecosystem of computational tools, including knowledge representation, data preparation, and model development. The …
-
Machine Learning Methods for Modeling Synthesizable Molecules
… tasks of (a) how to use ML to predict chemical reaction outcomes, and (b) how to build generative models to search for new molecules. We take a common approach to both tasks, building our ML models around existing powerful tools and abstractions from the field of chemistry, and in doing so, show …
-
Predicting Chemical Reactions at the MechanisticLevel through Deep Reinforcement Learning
Reaction prediction is a fundamental problem in chemistry. Previous work has mostly targeted chemical product prediction only, but did not elucidate any mechanisms or elementary steps from which the reaction proceeds. Here, we attempt to predict chemical mechanisms via deep reinforcement learning. …
-
Molecular Graph Representation Learning and Generation for Drug Discovery
… representation, in particular, property and reaction prediction. Here, we explore a transformer-style architecture for molecular representation, providing new tools to apply these models to graph-structured objects. Moving away from the traditional graph neural network paradigm, we …
-
Accelerating Materials Discovery with Machine Learning
… data-mined data set of solid-state synthesis reactions, we design a two-stage model to predict the products of inorganic reactions. We critically explore the performance of this model, showing that whilst the predictions fall short of the accuracy required to be chemically discriminative, the …
-
Towards algorithmic use of chemical data
… approaches can be used to study chemical reactions. In this thesis several research questions from the field of data science and graph theory are re-formulated for the chemistry-specific data. Firstly, the structure of chemical reactions data was studied using graph theory. It was found …
-
Accelerating the Design-Make-Test cycle of Drug Discovery with Machine Learning
… is to use deep learning models trained on patent reaction databases, but they suffer from being opaque black boxes. It is neither clear if the models are making correct predictions because they inferred the salient chemistry, nor is it clear which training data they are relying on to reach a …