Learning to Optimize Molecular Geometries Using Reinforcement Learning by Kabir Ahuja (10010761)

The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

S1 Data - by Haoqiang Liu (193675)

Spearman correlation coefficient results for classification algorithms (predicted probabilities) and regression algorithms (predicted IC50 values). by Sofia P. Miranda (11418930)

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Example medication days generated for patients P4 and P6, medication times (red dots), patient’s state—TRS score (blue line) with bounds for the states (red lines) and optimal stat... by Tomasz Gutowski (17200042)

Bivariate analysis using line plot for casing, bearing & impeller vs pressure. by Gaurav Sandeep Dave (21519884)

Optimizing Pharmacokinetic Property Prediction Based on Integrated Datasets and a Deep Learning Approach by Xiting Wang (9327613)

“…Results were also obtained using several other algorithms and independent validation datasets as a control study. …”

Optimizing Pharmacokinetic Property Prediction Based on Integrated Datasets and a Deep Learning Approach by Xiting Wang (9327613)

“…Results were also obtained using several other algorithms and independent validation datasets as a control study. …”

Optimizing Pharmacokinetic Property Prediction Based on Integrated Datasets and a Deep Learning Approach by Xiting Wang (9327613)

“…Results were also obtained using several other algorithms and independent validation datasets as a control study. …”

Classification results for all subsampling scenarios and algorithms for Gefitinib. by Sofia P. Miranda (11418930)

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Regression results for all combinations of subsampling scenarios and algorithms for Gefitinib. by Sofia P. Miranda (11418930)

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Average RMSE rank for all combinations of subsampling scenarios and algorithms. by Sofia P. Miranda (11418930)

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DMTD algorithm. by Yunhu Huang (21402795)

“…On the basis of EITO_E, we propose EITO_P algorithm using the PPO algorithm to optimize multiple objectives by designing reinforcement learning strategies, rewards, and value functions. …”

Summary of AUC values across all combinations of subsampling scenario and algorithm. by Sofia P. Miranda (11418930)

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Relative predictive performance when using default algorithm hyperparameters and all features vs. tuning hyperparameters or selecting features. by Stephen R. Piccolo (8367780)

Most informative genes for predicting cell-line responses for Gefitinib. by Sofia P. Miranda (11418930)

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Descriptions of the algorithms we tested and hyperparameters that we evaluated via nested cross validation. by Sofia P. Miranda (11418930)

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Pseudo Code of RBMO. by Chenyi Zhu (9383370)

The estimated optimism-corrected area under the receiver operating characteristic curve (OC-AUC-ROC), for predictive models developed by different machine learning algorithms and f... by Shiying You (12981374)

Minimum, mean and maximum RMSE value for each drug and algorithm combination, averaged across all subsampling scenarios. by Sofia P. Miranda (11418930)

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