CASynergy algorithm workflow. by Haitao Li (305080)

Phenotype frequencies for each mutant and for complementation testing. by McKenna Feltes (11242085)

TIR-Learner v3: New generation TE annotation program for identifying TIRs by Tianyu Lu (18856792)

Phenotype frequency and complementation for additional novel DY alleles. by McKenna Feltes (11242085)

Biological pathway enrichment analysis for key genes identified by the CASynergy algorithm in different cancer cell lines. by Haitao Li (305080)

Candidate algorithms included in the super learner libraries. by Vishalie Shah (7301909)

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Causal forest tuning parameters. by Vishalie Shah (7301909)

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Schematic diagram of random forest algorithm. by Imee V. Necesito (12749885)

Variable importance results from estimated causal forests. by Vishalie Shah (7301909)

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Mean prevalence of CoC across groups created using the k-means algorithm. by Shafayet Khan Shafee (22593191)

Heatmaps for classification analysis (two-part model). by Vishalie Shah (7301909)

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Heatmaps for classification analysis (participation and consumption models). by Vishalie Shah (7301909)

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Data Sheet 1_Causal contextual bandits with one-shot data integration.pdf by Chandrasekar Subramanian (20393715)

“…This new formalism provides a natural model for several real-world scenarios where parallel targeted experiments can be conducted and where some domain knowledge of causal relationships is available. …”

Causal Relationship between Potential Shift and Molecular Structure in Concentrated Electrolytes by Yumika Yokoyama (18422218)

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Causal Machine Learning Benchmark Datasets by Damian Machlanski (12255509)

“…<p dir="ltr">This collection includes four well-known datasets used to benchmark causal machine learning algorithms. The datasets are: IHDP [1], News [2], Twins [3], Jobs [4].…”

Evaluating the Effectiveness of Mobile Precision Push Services A User-Centric Behavioral Framework by Wang Peng (20617712)

“…While prior studies have focused on technical accuracy and personalization algorithms, limited attention has been paid to how experiential and perceptual factors collectively influence user engagement and behavioral outcomes.…”

Nonlinear Granger causality test for Volatility of Bitcoin based on the Parkinson volatility estimator and Bitcoin-based energy consumption. by Georgia Zournatzidou (22453552)

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Nonlinear Granger causality test for Volatility of Bitcoin based on the Garman-Klass volatility estimator and Bitcoin-based energy consumption. by Georgia Zournatzidou (22453552)

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Nonlinear Granger causality test for Volatility of Bitcoin based on the Rogers-Satchell volatility estimator and Bitcoin-based energy consumption. by Georgia Zournatzidou (22453552)

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Logarithm of each volatility estimator calculated based on daily Bitcoin prices, as well as the Cambridge Bitcoin-based Electricity Consumption Index (logarithmic transformation). by Georgia Zournatzidou (22453552)

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