Dan Garant
Artificial Intelligence · 2013–2019
A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 11 citations into it
- Causal Inference & Discovery — 8 citations into it
Whom Dan Garant trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Papers from Dan Garant's perspective
Ordered by how strongly the researchers Dan Garant trusts endorse each paper. Same corpus, a different order for every researcher.
- Causation, Prediction, and Search
- Causal Protein-Signaling Networks Derived from Multiparameter Single-Cell Data
- Investigating causal relations by econometric models and cross-spectral methods
- Causality : Objectives and Assessment
- Distinguishing Cause from Effect Using Observational Data: Methods and Benchmarks
- The max-min hill-climbing Bayesian network structure learning algorithm
- Can Nonrandomized Experiments Yield Accurate Answers? A Randomized Experiment Comparing Random and Nonrandom Assignments
- Causality
- Data from Paper “False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant”
- Three conditions under which experiments and observational studies produce comparable causal estimates: New findings from within‐study comparisons
Their papers
- The Case for Evaluating Causal Models Using Interventional Measures and Empirical Data (2019) — 56 citations
- Botnet detection based on traffic behavior analysis and flow intervals (2013) — 359 citations