activity
20202026
most citedIdentification Methods With Arbitrary Interventional Distributions as Inputs

2 citations · 7 across the 10 of their papers we have counts for

collaborators

10 papers

cs.LG2026

Macaron-V1: Towards Open Continual Learning with Self-Improvement and Mixture-of-LoRA

Mind Lab, :, Vin Bo +80

Macaron-V1 is an open agent-model family for experiential intelligence: learning from experience in real environments and continuing to learn after deployment. It is organized arou…

stat.ME2024

Zero Inflation as a Missing Data Problem: a Proxy-based Approach

Trung Phung, Jaron J. R. Lee, Opeyemi Oladapo-Shittu +8

A common type of zero-inflated data has certain true values incorrectly replaced by zeros due to data recording conventions (rare outcomes assumed to be absent) or details of data…

stat.ME2024

A General Identification Algorithm For Data Fusion Problems Under Systematic Selection

Jaron J. R. Lee, AmirEmad Ghassami, Ilya Shpitser

Causal inference is made challenging by confounding, selection bias, and other complications. A common approach to addressing these difficulties is the inclusion of auxiliary data…

cs.RO2023★ 1 cited

An Introduction to Causal Inference Methods for Observational Human-Robot Interaction Research

Jaron J. R. Lee, Gopika Ajaykumar, Ilya Shpitser +1

Quantitative methods in Human-Robot Interaction (HRI) research have primarily relied upon randomized, controlled experiments in laboratory settings. However, such experiments are n…

stat.ME2023★ 2 cited

Ananke: A Python Package For Causal Inference Using Graphical Models

Jaron J. R. Lee, Rohit Bhattacharya, Razieh Nabi +1

We implement Ananke: an object-oriented Python package for causal inference with graphical models. At the top of our inheritance structure is an easily extensible Graph class that…

cs.LG2022

Off-Policy Evaluation in Embedded Spaces

Jaron J. R. Lee, David Arbour, Georgios Theocharous

Off-policy evaluation methods are important in recommendation systems and search engines, where data collected under an existing logging policy is used to estimate the performance…

stat.ME2021

Markov-Restricted Analysis of Randomized Trials with Non-Monotone Missing Binary Outcomes

Jaron J. R. Lee, Agatha S. Mallett, Ilya Shpitser +3

Scharfstein et al. (2021) developed a sensitivity analysis model for analyzing randomized trials with repeatedly measured binary outcomes that are subject to nonmonotone missingnes…

stat.ME2020

Path Dependent Structural Equation Models

Ranjani Srinivasan, Jaron Lee, Rohit Bhattacharya +2

Causal analyses of longitudinal data generally assume that the qualitative causal structure relating variables remains invariant over time. In structured systems that transition be…

cs.LG2020★ 2 cited

A Semiparametric Approach to Interpretable Machine Learning

Numair Sani, Jaron Lee, Razieh Nabi +1

Black box models in machine learning have demonstrated excellent predictive performance in complex problems and high-dimensional settings. However, their lack of transparency and i…

stat.ML2020★ 2 cited

Identification Methods With Arbitrary Interventional Distributions as Inputs

Jaron J. R. Lee, Ilya Shpitser

Causal inference quantifies cause-effect relationships by estimating counterfactual parameters from data. This entails using \emph{identification theory} to establish a link betwee…