David Page
18 papers · 2003–2025 · 9 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (39) 🏃 Academic Marathon · Ultra 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
🌱
Topic Pioneer
🌟
Keyword Trendsetter Combo
(4)
🧭
Keyword Pioneer
📈
Trend Setter
🌈
Renaissance Researcher
(6)
🔥
Unstoppable · Bronze
🗃️
Keyword Collector
(112)
💎
Century Club · Bronze
Top co-authors
Research topics
Machine Learning
(15)
Core Methods
(13)
Artificial Intelligence
(9)
Core AI
(6)
Optimization & Theory
(6)
Mathematics & Optimization
(5)
Bayesian & Probabilistic · Machine Learning
(5)
Healthcare & Medicine
(4)
Bayesian & Probabilistic · Artificial Intelligence
(4)
Knowledge & Reasoning
(3)
Clinical
(3)
Learning Types
(3)
Mathematics
(3)
Deep Learning
(2)
Reasoning
(2)
Keywords
graphical model
(5)
causal inference
(3)
bayesian inference
(3)
bayesian network
(2)
electronic health record
(2)
causal discovery
(2)
feature selection
(2)
probabilistic graphical model
(2)
binary classification
(1)
structured prediction
(1)
approximate inference
(1)
structure learning
(1)
parameter estimation
(1)
em algorithm
(1)
temporal modeling
(1)
convex optimization
(1)
variable selection
(1)
sparse estimation
(1)
ising model
(1)
knowledge representation
(1)
Papers
Temporal Inverse Probability Weighting for Causal Discovery in Controlled Before–After Studies: Discovering ADEs in Generics
CLeaR 2025
MALADE: Orchestration of LLM-powered Agents with Retrieval Augmented Generation for Pharmacovigilance
MLHC 2024
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models
NeurIPS 2024
Variable importance matching for causal inference
UAI 2023
CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods
ICML 2020
AUCμ: A Performance Metric for Multi-Class Machine Learning Models
ICML 2019
Causal Structure Learning via Temporal Markov Networks
PGM 2018
Temporal Poisson Square Root Graphical Models
ICML 2018
A Screening Rule for l1-Regularized Ising Model Estimation
NeurIPS 2017
Baseline Regularization for Computational Drug Repositioning with Longitudinal Observational Data
IJCAI 2016
Structure-Leveraged Methods in Breast Cancer Risk Prediction
JMLR 2016
Learning Heterogeneous Hidden Markov Random Fields
AISTATS 2014
Multiple Testing under Dependence via Semiparametric Graphical Models
ICML 2014
Bayesian Estimation of Latently-grouped Parameters in Undirected Graphical Models
NeurIPS 2013
High-Dimensional Structured Feature Screening Using Binary Markov Random Fields
AISTATS 2012
Multiplicative Forests for Continuous-Time Processes
NeurIPS 2012
Exploiting Product Distributions to Identify Relevant Variables of Correlation Immune Functions
JMLR 2009
ILP: A Short Look Back and a Longer Look Forward
JMLR 2003