You can also find my papers on Google Scholar

• Multi-Armed Bandits with Network Interference
  Abhineet Agarwal, Anish Agarwal, Lorenzo Masoero, Justin Whitehouse.
  Venue: Accepted to NeurIPS, 2024

• Tree Transfomers: Combining Tree-Based Models with Mixture of Experts and Transformers for Improved Accuracy and Inference Cost
  Abhineet Agarwal, Bin Yu (Link Forthcoming)
  Venue: In Submission to Journal of Machine Learning Research (JMLR), 2024

• ED-Copilot: Reduce Emergency Wait Time with Language Model Diagnostic Assistance
  Liwen Sun, Abhineet Agarwal, Aaron Kornblith, Bin Yu, Chenyan Xiong.
  Venue: ICML, 2024

• Synthetic Combinations: A Causal Inference Framework for Combinatiorial Interventions
  Abhineet Agarwal, Anish Agarwal, Suhas Vijaykumar
  Venue: NeurIPS, 2023, extended version in submission to Econometrica

• Fast Interpretable Greedy Tree Sums (FIGS)
  Abhineet Agarwal, et al.
  Venue: Accepted to Proceedings of the National Academy of Sciences (PNAS), 2024

• MDI+: A Flexible Random Forest-Based Feature Importance Framework
  Abhineet Agarwal, Ana Kenney, Yan Shuo Tan, Tiffany Tang, Bin Yu
  Venue: In submission to Journal of the American Statistical Association (JASA), 2023

• Epistasis regulates genetic control of cardiac hypertrophy
  Tiffany Tang, …, Abhineet Agarwal,… Bin Yu
  Venue: Nature Cardiovascular Research, 2023

• Hierarchical Shrinkage: Improving the Accuracy and Interpretability of Tree-Based Models
  Abhineet Agarwal, Yan Shuo Tan, Omer Ronen, Chandan Singh, Bin Yu
  Venue: ICML, 2022. (Oral Presentation)

• Veridical Flow: A Python Package for Building Trustworthy Data Science Pipelines with PCS
  James Duncan, Rush Kapoor, Abhineet Agarwal, Chandan Singh, Bin Yu
  Venue: Journal of Open Source Software, 2022.

• A Cautionary Tale on the Fitting Decision Trees to Additive Models: Generalization Lower Bounds
  Yan Shuo Tan, Abhineet Agarwal, Bin Yu
  Venue: AISTATS, 2022.