Fig. 3: Comparison of single task and multi-task learning models. | npj Computational Materials

Fig. 3: Comparison of single task and multi-task learning models.

From: Gas permeability, diffusivity, and solubility in polymers: Simulation-experiment data fusion and multi-task machine learning

Fig. 3

a Model inputs. This schema illustrates the train and test splits for two model variants: Regular Single Task (ST) and data-fused Multi-Task (MT) models. In the ST models, solely experimental gas permeability data is incorporated. Conversely, the MT model encompasses a possible amalgamation of experimental gas diffusivity and solubility, along with simulated gas permeability, diffusivity, and solubility data. b Benchmark models. Four distinct models were developed to assess the impact of MT learning. The first model (ST) exclusively incorporated experimental gas permeability data. In contrast, the subsequent MT models progressively integrated additional data. The presence of each data type in the model is indicated by a black checkmark. Here, P, D, and S represent gas permeability, diffusivity, and solubility, respectively. The abbreviation expt corresponds to experimental data, while sim signifies simulation data.

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