Marinka Zitnik

CoRR, 2024

Repurposing Foundation Model for Generalizable Medical Time Series Classification.

[BibT_eX]

[DOI]

CoRR, 2024

How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities.

[BibT_eX]

[DOI]

CoRR, 2024

Quantum-machine-assisted Drug Discovery: Survey and Perspective.

[BibT_eX]

[DOI]

CoRR, 2024

Composable Interventions for Language Models.

[BibT_eX]

[DOI]

Arinbjorn Kolbeinsson

Jonathan Richard Schwarz

CoRR, 2024

TrialBench: Multi-Modal Artificial Intelligence-Ready Clinical Trial Datasets.

[BibT_eX]

[DOI]

CoRR, 2024

Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate?

[BibT_eX]

[DOI]

CoRR, 2024

Empowering Biomedical Discovery with AI Agents.

[BibT_eX]

[DOI]

Shanghua Gao

Ada Fang

Yepeng Huang

Valentina Giunchiglia

Ayush Noori

Jonathan Richard Schwarz

Yasha Ektefaie

Jovana Kondic

CoRR, 2024

Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium.

[BibT_eX]

[DOI]

CoRR, 2024

UniTS: Building a Unified Time Series Model.

[BibT_eX]

[DOI]

CoRR, 2024

TrustLLM: Trustworthiness in Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

Graph Adversarial Diffusion Convolution.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Position: TrustLLM: Trustworthiness in Large Language Models.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Let's Think Outside the Box: Exploring Leap-of-Thought in Large Language Models with Creative Humor Generation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

MoExtend: Tuning New Experts for Modality and Task Extension.

[BibT_eX]

[DOI]

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics, 2024

2023

Structure-inducing pre-training.

[BibT_eX]

[DOI]

Matthew B. A. McDermott

Brendan Yap

Peter Szolovits

Nat. Mac. Intell., June, 2023

<tt>Metapaths</tt>: similarity search in heterogeneous knowledge graphs via meta-paths.

[BibT_eX]

[DOI]

Bioinform., May, 2023

Multimodal learning with graphs.

[BibT_eX]

[DOI]

Nat. Mac. Intell., April, 2023

Biomonitoring and precision health in deep space supported by artificial intelligence.

[BibT_eX]

[DOI]

Aenor Sawyer

Casey S. Greene

Amina Ann Qutub

Jon Rask

Nat. Mac. Intell., March, 2023

Biological research and self-driving labs in deep space supported by artificial intelligence.

[BibT_eX]

[DOI]

Robert J. Reynolds

Nat. Mac. Intell., March, 2023

Multimodal representation learning for predicting molecule-disease relations.

[BibT_eX]

[DOI]

Jun Wen

Vidul Ayakulangara Panickan

Everett Neil Rush

Bioinform., February, 2023

Extending the Nested Model for User-Centric XAI: A Design Study on GNN-based Drug Repurposing.

[BibT_eX]

[DOI]

IEEE Trans. Vis. Comput. Graph., 2023

Scientific discovery in the age of artificial intelligence.

[BibT_eX]

[DOI]

Nat., 2023

Multimodal learning on graphs for disease relation extraction.

[BibT_eX]

[DOI]

J. Biomed. Informatics, 2023

Is Ignorance Bliss? The Role of Post Hoc Explanation Faithfulness and Alignment in Model Trust in Laypeople and Domain Experts.

[BibT_eX]

[DOI]

CoRR, 2023

Graph AI in Medicine.

[BibT_eX]

[DOI]

CoRR, 2023

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.

[BibT_eX]

[DOI]

Aria Mansouri Tehrani

Kamyar Azizzadenesheli

CoRR, 2023

Full-Atom Protein Pocket Design via Iterative Refinement.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning Generalized Medical Image Representations Through Image-Graph Contrastive Pretraining.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning for Health, 2023

The 3rd Workshop on Graph Learning Benchmarks (GLB 2023).

[BibT_eX]

[DOI]

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Domain Adaptation for Time Series Under Feature and Label Shifts.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

GNNDelete: A General Strategy for Unlearning in Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Editorial Deep Learning and Graph Embeddings for Network Biology.

[BibT_eX]

[DOI]

Pietro Hiram Guzzi

IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Geometric multimodal representation learning.

[BibT_eX]

[DOI]

CoRR, 2022

Evaluating Explainability for Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2022

Rethinking Stability for Attribution-based Explanations.

[BibT_eX]

[DOI]

CoRR, 2022

A manifesto on explainability for artificial intelligence in medicine.

[BibT_eX]

[DOI]

Artif. Intell. Medicine, 2022

Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency.

[BibT_eX]

[DOI]

Ziyuan Zhao

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

OpenXAI: Towards a Transparent Evaluation of Model Explanations.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Graph-Guided Network for Irregularly Sampled Multivariate Time Series.

[BibT_eX]

[DOI]

Marko Zeman

Proceedings of the Tenth International Conference on Learning Representations, 2022

Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods.

[BibT_eX]

[DOI]

Chirag Agarwal

Himabindu Lakkaraju

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Guest Editorial: AI for COVID-19.

[BibT_eX]

[DOI]

Yuxiao Dong

IEEE Trans. Big Data, 2021

Contrastive learning improves critical event prediction in COVID-19 patients.

[BibT_eX]

[DOI]

Jessica K. De Freitas

Patterns, 2021

Population-scale identification of differential adverse events before and during a pandemic.

[BibT_eX]

[DOI]

Marissa Sumathipala

Nat. Comput. Sci., 2021

Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs.

[BibT_eX]

[DOI]

Robert J. Reynolds

CoRR, 2021

Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health.

[BibT_eX]

[DOI]

Aenor Sawyer

Casey S. Greene

Amina Ann Qutub

Jon Rask

CoRR, 2021

Towards a Rigorous Theoretical Analysis and Evaluation of GNN Explanations.

[BibT_eX]

[DOI]

Chirag Agarwal

Himabindu Lakkaraju

CoRR, 2021

Deep Contextual Learners for Protein Networks.

[BibT_eX]

[DOI]

Michelle M. Li

CoRR, 2021

Representation Learning for Networks in Biology and Medicine: Advancements, Challenges, and Opportunities.

[BibT_eX]

[DOI]

Michelle M. Li

Kexin Huang

CoRR, 2021

Rethinking Relational Encoding in Language Model: Pre-Training for General Sequences.

[BibT_eX]

[DOI]

Matthew B. A. McDermott

Brendan Yap

Peter Szolovits

CoRR, 2021

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics.

[BibT_eX]

[DOI]

CoRR, 2021

Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients.

[BibT_eX]

[DOI]

Jessica K. De Freitas

CoRR, 2021

DeepPurpose: a deep learning library for drug-target interaction prediction.

[BibT_eX]

[DOI]

Bioinform., 2021

Towards a unified framework for fair and stable graph representation learning.

[BibT_eX]

[DOI]

Chirag Agarwal

Himabindu Lakkaraju

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development.

[BibT_eX]

[DOI]

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Graph Based Machine Learning for Healthcare: State of the Art, Challenges, and Opportunities.

[BibT_eX]

[DOI]

Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021

2020

Interpretability of machine learning-based prediction models in healthcare.

[BibT_eX]

[DOI]

WIREs Data Mining Knowl. Discov., 2020

MolDesigner: Interactive Design of Efficacious Drugs with Deep Learning.

[BibT_eX]

[DOI]

CoRR, 2020

SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks.

[BibT_eX]

[DOI]

CoRR, 2020

Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19.

[BibT_eX]

[DOI]

Rebecca Marlene Baron

Dina Ghiassian

Joseph Loscalzo

Albert-László Barabási

CoRR, 2020

GNNGuard: Defending Graph Neural Networks against Adversarial Attacks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Graph Meta Learning via Local Subgraphs.

[BibT_eX]

[DOI]

Kexin Huang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Open Graph Benchmark: Datasets for Machine Learning on Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Subgraph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Strategies for Pre-training Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities.

[BibT_eX]

[DOI]

Inf. Fusion, 2019

Pre-training Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

GNN Explainer: A Tool for Post-hoc Explanation of Graph Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2019

Cross-type biomedical named entity recognition with deep multi-task learning.

[BibT_eX]

[DOI]

Bioinform., 2019

GNNExplainer: Generating Explanations for Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

Querying Complex Networks in Vector Space.

[BibT_eX]

[DOI]

CoRR, 2018

Network Enhancement: a general method to denoise weighted biological networks.

[BibT_eX]

[DOI]

CoRR, 2018

Prioritizing network communities.

[BibT_eX]

[DOI]

Rok Sosic

CoRR, 2018

Modeling polypharmacy side effects with graph convolutional networks.

[BibT_eX]

[DOI]

Monica Agrawal

Bioinform., 2018

Large-scale analysis of disease pathways in the human interactome.

[BibT_eX]

[DOI]

Monica Agrawal

Proceedings of the Biocomputing 2018: Proceedings of the Pacific Symposium, 2018

Embedding Logical Queries on Knowledge Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning Structural Node Embeddings via Diffusion Wavelets.

[BibT_eX]

[DOI]

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

2017

Spectral Graph Wavelets for Structural Role Similarity in Networks.

[BibT_eX]

[DOI]

CoRR, 2017

Predicting multicellular function through multi-layer tissue networks.

[BibT_eX]

[DOI]

Bioinform., 2017

Scalable non-negative matrix tri-factorization.

[BibT_eX]

[DOI]

Andrej Copar

BioData Min., 2017

2016

The infinite mixtures of food products.

[BibT_eX]

[DOI]

XRDS, 2016

The Brownian wanderlust of things.

[BibT_eX]

[DOI]

XRDS, 2016

Jumping across biomedical contexts using compressive data fusion.

[BibT_eX]

[DOI]

Bioinform., 2016

Orthogonal matrix factorization enables integrative analysis of multiple RNA binding proteins.

[BibT_eX]

[DOI]

Bioinform., 2016

Collective Pairwise Classification for Multi-Way Analysis of Disease and Drug Data.

[BibT_eX]

[DOI]

Proceedings of the Biocomputing 2016: Proceedings of the Pacific Symposium, 2016

2015

Sieve-based relation extraction of gene regulatory networks from biological literature.

[BibT_eX]

[DOI]

BMC Bioinform., December, 2015

Gene Prioritization by Compressive Data Fusion and Chaining.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2015

Data Fusion by Matrix Factorization.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2015

Data Imputation in Epistatic MAPs by Network-Guided Matrix Completion.

[BibT_eX]

[DOI]

J. Comput. Biol., 2015

According to sensor 22, Benny is preparing dinner.

[BibT_eX]

[DOI]

Lara Zupan

XRDS, 2015

Sorry kids, Iron Man's superpowers aren't unique.

[BibT_eX]

[DOI]

Lara Zupan

XRDS, 2015

Hidden genes: understanding cancer data with matrix factorization.

[BibT_eX]

[DOI]

XRDS, 2015

Gene network inference by fusing data from diverse distributions.

[BibT_eX]

[DOI]

Bioinform., 2015

2014

The anatomy of a human disease network.

[BibT_eX]

[DOI]

XRDS, 2014

Dynamics of news from the <i>New York Times</i>.

[BibT_eX]

[DOI]

XRDS, 2014

Exploring data with topological tools.

[BibT_eX]

[DOI]

XRDS, 2014

Efficient sensor placement for environmental monitoring.

[BibT_eX]

[DOI]

XRDS, 2014

Gene network inference by probabilistic scoring of relationships from a factorized model of interactions.

[BibT_eX]

[DOI]

Bioinform., 2014

Imputation of Quantitative Genetic Interactions in Epistatic MAPs by Interaction Propagation Matrix Completion.

[BibT_eX]

[DOI]

Proceedings of the Research in Computational Molecular Biology, 2014

Matrix Factorization-Based Data Fusion for Gene Function Prediction in Baker's Yeast and Slime Mold.

[BibT_eX]

[DOI]

Proceedings of the Biocomputing 2014: Proceedings of the Pacific Symposium, 2014

2013

Orange: data mining toolbox in python.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2013

On constructing the tree of life.

[BibT_eX]

[DOI]

XRDS, 2013

Zero-knowledge Proofs.

[BibT_eX]

[DOI]

XRDS, 2013

Matrix function: a "VIP" in linear algebra and its applications.

[BibT_eX]

[DOI]

XRDS, 2013

Extracting Gene Regulation Networks Using Linear-Chain Conditional Random Fields and Rules.

[BibT_eX]

[DOI]

Proceedings of the BioNLP Shared Task 2013 Workshop, Sofia, 2013

2012

NIMFA: A Python Library for Nonnegative Matrix Factorization.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2012

Iterative numerical methods for nonlinear systems.

[BibT_eX]

[DOI]

XRDS, 2012

Using sentiment analysis to improve business operations.

[BibT_eX]

[DOI]