NewEvery arXiv paper, its researchers & institutions — mapped.
papers

Publications (29)

q-bio.OT2018

An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge

Houssam Nassif, Hassan Al-Ali, Sawsan Khuri +2

cs.CL2024

MALADE: Orchestration of LLM-powered Agents with Retrieval Augmented Generation for Pharmacovigilance

Jihye Choi, Nils Palumbo, Prasad Chalasani +4

stat.AP2016

Computational Drug Repositioning Using Continuous Self-controlled Case Series

Zhaobin Kuang, James Thomson, Michael Caldwell +3

cs.IR2019

A Simple Text Mining Approach for Ranking Pairwise Associations in Biomedical Applications

Finn Kuusisto, John Steill, Zhaobin Kuang +3

stat.ML2017

An Efficient Pseudo-likelihood Method for Sparse Binary Pairwise Markov Network Estimation

Sinong Geng, Zhaobin Kuang, David Page

cs.DB2019

AutoBlock: A Hands-off Blocking Framework for Entity Matching

Wei Zhang, Hao Wei, Bunyamin Sisman +3

cs.AI2023

Neural Markov Prolog

Alexander Thomson, David Page

cs.CV2026

Cosmos 3: Omnimodal World Models for Physical AI

NVIDIA, :, Aditi +293

cs.LG2012

Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug Events

Jesse Davis, Vitor Santos Costa, Peggy Peissig +3

stat.ME2023

Variable Importance Matching for Causal Inference

Quinn Lanners, Harsh Parikh, Alexander Volfovsky +2

stat.ML2025

On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models

Boyao Li, Alexander J. Thomson, Houssam Nassif +2

cs.LG2022

High-Throughput Approach to Modeling Healthcare Costs Using Electronic Healthcare Records

Alex Taylor, Ross Kleiman, Scott Hebbring +2

stat.ME2012

Graphical-model Based Multiple Testing under Dependence, with Applications to Genome-wide Association Studies

Jie Liu, Chunming Zhang, Catherine McCarty +3

cs.LG2020

Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error

Sinong Geng, Zhaobin Kuang, Jie Liu +2

q-bio.QM2019

High-Throughput Machine Learning from Electronic Health Records

Ross S. Kleiman, Paul S. Bennett, Peggy L. Peissig +5

cs.AI2012

Learning Bayesian Network Structure from Correlation-Immune Data

Eric Lantz, Soumya Ray, David Page

cs.LG2012

Unachievable Region in Precision-Recall Space and Its Effect on Empirical Evaluation

Kendrick Boyd, Vitor Santos Costa, Jesse Davis +1

cs.LG2020

CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods

Wei Zhang, Thomas Kobber Panum, Somesh Jha +2

cs.CV2025

Cosmos World Foundation Model Platform for Physical AI

NVIDIA, :, Niket Agarwal +76

cs.LG2020

Temporal Poisson Square Root Graphical Models

Sinong Geng, Zhaobin Kuang, Peggy Peissig +1

cs.AI2012

CLP(BN): Constraint Logic Programming for Probabilistic Knowledge

Vitor Santos Costa, David Page, Maleeha Qazi +1

cs.LG2023

Differentially Private Multi-Site Treatment Effect Estimation

Tatsuki Koga, Kamalika Chaudhuri, David Page

cs.CV2025

Training Video Foundation Models with NVIDIA NeMo

Zeeshan Patel, Ethan He, Parth Mannan +26

q-bio.QM2019

Machine Learning to Predict Developmental Neurotoxicity with High-throughput Data from 2D Bio-engineered Tissues

Finn Kuusisto, Vitor Santos Costa, Zhonggang Hou +3

hep-th2008

Phases Of N=2 Theories In 1+1 Dimensions With Boundary

Manfred Herbst, Kentaro Hori, David Page

cs.LG2021

Predicting Drug-Drug Interactions from Heterogeneous Data: An Embedding Approach

Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli +2

cs.LG2018

Privacy-Preserving Collaborative Prediction using Random Forests

Irene Giacomelli, Somesh Jha, Ross Kleiman +2

stat.ML2025

Probably Approximately Correct Causal Discovery

Mian Wei, Somesh Jha, David Page

cs.LG2020

Beyond Textual Data: Predicting Drug-Drug Interactions from Molecular Structure Images using Siamese Neural Networks

Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli +2