Team ULjubljana's Solution to the JRS 2012 Data Mining Competition. - Jure Zbontar; Marinka Zitnik; Miha Zidar; Gregor Majcen; Matic Potocnik; Blaz Zupan (RSCTC, 2012)

Using sentiment analysis to improve business operations. - Marinka Zitnik (XRDS, 2012)

Iterative numerical methods for nonlinear systems. - Marinka Zitnik (XRDS, 2012)

NIMFA: A Python Library for Nonnegative Matrix Factorization. - Marinka Zitnik; Blaz Zupan (J. Mach. Learn. Res., 2012)

Extracting Gene Regulation Networks Using Linear-Chain Conditional Random Fields and Rules. - Slavko Zitnik; Marinka Zitnik; Blaz Zupan; Marko Bajec (BioNLP@ACL (Shared Task), 2013)

Matrix function: a "VIP" in linear algebra and its applications. - Marinka Zitnik (XRDS, 2013)

Zero-knowledge Proofs. - Marinka Zitnik (XRDS, 2013)

On constructing the tree of life. - Marinka Zitnik (XRDS, 2013)

Orange: data mining toolbox in python. - Janez Demsar; Tomaz Curk; Ales Erjavec; Crtomir Gorup; Tomaz Hocevar; Mitar Milutinovic; Martin Mozina; Matija Polajnar; Marko Toplak; Anze Staric; Miha Stajdohar; Lan Umek; et al. (J. Mach. Learn. Res., 2013)

Matrix Factorization-Based Data Fusion for Gene Function Prediction in Baker's Yeast and Slime Mold. - Marinka Zitnik; Blaz Zupan (Pacific Symposium on Biocomputing, 2014)

Imputation of Quantitative Genetic Interactions in Epistatic MAPs by Interaction Propagation Matrix Completion. - Marinka Zitnik; Blaz Zupan (RECOMB, 2014)

Gene network inference by probabilistic scoring of relationships from a factorized model of interactions. - Marinka Zitnik; Blaz Zupan (Bioinform., 2014)

Efficient sensor placement for environmental monitoring. - Marinka Zitnik (XRDS, 2014)

Exploring data with topological tools. - Marinka Zitnik (XRDS, 2014)

Dynamics of news from the New York Times. - Marinka Zitnik (XRDS, 2014)

The anatomy of a human disease network. - Marinka Zitnik (XRDS, 2014)

Gene network inference by fusing data from diverse distributions. - Marinka Zitnik; Blaz Zupan (Bioinform., 2015)

Hidden genes: understanding cancer data with matrix factorization. - Marinka Zitnik (XRDS, 2015)

Sorry kids, Iron Man's superpowers aren't unique. - Lara Zupan; Marinka Zitnik (XRDS, 2015)

According to sensor 22, Benny is preparing dinner. - Lara Zupan; Marinka Zitnik (XRDS, 2015)

Data Imputation in Epistatic MAPs by Network-Guided Matrix Completion. - Marinka Zitnik; Blaz Zupan (J. Comput. Biol., 2015)

Data Fusion by Matrix Factorization. - Marinka Zitnik; Blaz Zupan (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Gene Prioritization by Compressive Data Fusion and Chaining. - Marinka Zitnik; Edward A. Nam; Christopher Dinh; Adam Kuspa; Gad Shaulsky; Blaz Zupan (PLoS Comput. Biol., 2015)

Sieve-based relation extraction of gene regulatory networks from biological literature. - Slavko Zitnik; Marinka Zitnik; Blaz Zupan; Marko Bajec (BMC Bioinform., 2015)

Collective Pairwise Classification for Multi-Way Analysis of Disease and Drug Data. - Marinka Zitnik; Blaz Zupan (PSB, 2016)

Orthogonal matrix factorization enables integrative analysis of multiple RNA binding proteins. - Martin Strazar; Marinka Zitnik; Blaz Zupan; Jernej Ule; Tomaz Curk (Bioinform., 2016)

Jumping across biomedical contexts using compressive data fusion. - Marinka Zitnik; Blaz Zupan (Bioinform., 2016)

The Brownian wanderlust of things. - Marinka Zitnik (XRDS, 2016)

The infinite mixtures of food products. - Marinka Zitnik (XRDS, 2016)

Scalable non-negative matrix tri-factorization. - Andrej Copar; Marinka Zitnik; Blaz Zupan (BioData Min., 2017)

Predicting multicellular function through multi-layer tissue networks. - Marinka Zitnik; Jure Leskovec (Bioinform., 2017)

Spectral Graph Wavelets for Structural Role Similarity in Networks. - Claire Donnat; Marinka Zitnik; David Hallac; Jure Leskovec (CoRR, 2017)

Learning Structural Node Embeddings via Diffusion Wavelets. - Claire Donnat; Marinka Zitnik; David Hallac; Jure Leskovec (KDD, 2018)

Embedding Logical Queries on Knowledge Graphs. - William L. Hamilton; Payal Bajaj; Marinka Zitnik; Dan Jurafsky; Jure Leskovec (NeurIPS, 2018)

Large-scale analysis of disease pathways in the human interactome. - Monica Agrawal; Marinka Zitnik; Jure Leskovec (PSB, 2018)

Modeling polypharmacy side effects with graph convolutional networks. - Marinka Zitnik; Monica Agrawal; Jure Leskovec (Bioinform., 2018)

Prioritizing network communities. - Marinka Zitnik; Rok Sosic; Jure Leskovec (CoRR, 2018)

Network Enhancement: a general method to denoise weighted biological networks. - Bo Wang 044; Armin Pourshafeie; Marinka Zitnik; Junjie Zhu; Carlos D. Bustamante; Serafim Batzoglou; Jure Leskovec (CoRR, 2018)

Querying Complex Networks in Vector Space. - William L. Hamilton; Payal Bajaj; Marinka Zitnik; Dan Jurafsky; Jure Leskovec (CoRR, 2018)

GNNExplainer: Generating Explanations for Graph Neural Networks. - Zhitao Ying; Dylan Bourgeois; Jiaxuan You; Marinka Zitnik; Jure Leskovec (NeurIPS, 2019)

Cross-type biomedical named entity recognition with deep multi-task learning. - Xuan Wang 008; Yu Zhang 044; Xiang Ren 001; Yuhao Zhang 004; Marinka Zitnik; Jingbo Shang; Curtis P. Langlotz; Jiawei Han 001 (Bioinform., 2019)

GNN Explainer: A Tool for Post-hoc Explanation of Graph Neural Networks. - Rex Ying; Dylan Bourgeois; Jiaxuan You; Marinka Zitnik; Jure Leskovec (CoRR, 2019)

Pre-training Graph Neural Networks. - Weihua Hu; Bowen Liu 014; Joseph Gomes; Marinka Zitnik; Percy Liang; Vijay S. Pande; Jure Leskovec (CoRR, 2019)

Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities. - Marinka Zitnik; Francis Nguyen; Bo Wang 044; Jure Leskovec; Anna Goldenberg; Michael M. Hoffman (Inf. Fusion, 2019)

Strategies for Pre-training Graph Neural Networks. - Weihua Hu; Bowen Liu 014; Joseph Gomes; Marinka Zitnik; Percy Liang; Vijay S. Pande; Jure Leskovec (ICLR, 2020)

Subgraph Neural Networks. - Emily Alsentzer; Samuel G. Finlayson; Michelle M. Li; Marinka Zitnik (NeurIPS, 2020)

Open Graph Benchmark: Datasets for Machine Learning on Graphs. - Weihua Hu; Matthias Fey; Marinka Zitnik; Yuxiao Dong; Hongyu Ren; Bowen Liu 014; Michele Catasta; Jure Leskovec (NeurIPS, 2020)

Graph Meta Learning via Local Subgraphs. - Kexin Huang; Marinka Zitnik (NeurIPS, 2020)

GNNGuard: Defending Graph Neural Networks against Adversarial Attacks. - Xiang Zhang 012; Marinka Zitnik (NeurIPS, 2020)

Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19. - Deisy Morselli Gysi; Ítalo Do Valle; Marinka Zitnik; Asher Ameli; Xiao Gan; Onur Varol; Helia Sanchez; Rebecca Marlene Baron; Dina Ghiassian; Joseph Loscalzo; Albert-László Barabási (CoRR, 2020)

SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks. - Kexin Huang; Cao Xiao; Lucas Glass; Marinka Zitnik; Jimeng Sun 001 (CoRR, 2020)

MolDesigner: Interactive Design of Efficacious Drugs with Deep Learning. - Kexin Huang; Tianfan Fu; Dawood Khan; Ali Abid; Ali Abdalla; Abubakar Abid; Lucas M. Glass; Marinka Zitnik; Cao Xiao; Jimeng Sun 001 (CoRR, 2020)

Interpretability of machine learning-based prediction models in healthcare. - Gregor Stiglic; Primoz Kocbek; Nino Fijacko; Marinka Zitnik; Katrien Verbert; Leona Cilar (WIREs Data Mining Knowl. Discov., 2020)

Graph Based Machine Learning for Healthcare: State of the Art, Challenges, and Opportunities. - Yuan Luo 001; Fei Wang 001; Marinka Zitnik; Shuiwang Ji (AMIA, 2021)

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development. - Kexin Huang; Tianfan Fu; Wenhao Gao 001; Yue Zhao 016; Yusuf H. Roohani; Jure Leskovec; Connor W. Coley; Cao Xiao; Jimeng Sun 001; Marinka Zitnik (NeurIPS Datasets and Benchmarks, 2021)

Towards a unified framework for fair and stable graph representation learning. - Chirag Agarwal; Himabindu Lakkaraju; Marinka Zitnik (UAI, 2021)

DeepPurpose: a deep learning library for drug-target interaction prediction. - Kexin Huang; Tianfan Fu; Lucas M. Glass; Marinka Zitnik; Cao Xiao; Jimeng Sun 001 (Bioinform., 2021)

Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients. - Tingyi Wanyan; Hossein Honarvar; Suraj K. Jaladanki; Chengxi Zang; Nidhi Naik; Sulaiman Somani; Jessica K. De Freitas; Ishan Paranjpe; Akhil Vaid; Riccardo Miotto; Girish N. Nadkarni; Marinka Zitnik; et al. (CoRR, 2021)

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics. - Kexin Huang; Tianfan Fu; Wenhao Gao 001; Yue Zhao 016; Yusuf H. Roohani; Jure Leskovec; Connor W. Coley; Cao Xiao; Jimeng Sun 001; Marinka Zitnik (CoRR, 2021)

Rethinking Relational Encoding in Language Model: Pre-Training for General Sequences. - Matthew B. A. McDermott; Brendan Yap; Peter Szolovits; Marinka Zitnik (CoRR, 2021)

Representation Learning for Networks in Biology and Medicine: Advancements, Challenges, and Opportunities. - Michelle M. Li; Kexin Huang; Marinka Zitnik (CoRR, 2021)

Deep Contextual Learners for Protein Networks. - Michelle M. Li; Marinka Zitnik (CoRR, 2021)

Towards a Rigorous Theoretical Analysis and Evaluation of GNN Explanations. - Chirag Agarwal; Marinka Zitnik; Himabindu Lakkaraju (CoRR, 2021)

Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health. - Ryan T. Scott; Erik L. Antonsen; Lauren M. Sanders; Jaden J. A. Hastings; Seung-Min Park; Graham Mackintosh; Robert J. Reynolds; Adrienne L. Hoarfrost; Aenor Sawyer; Casey S. Greene; Benjamin S. Glicksberg; Corey A. Theriot; et al. (CoRR, 2021)

Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs. - Lauren M. Sanders; Jason H. Yang; Ryan T. Scott; Amina Ann Qutub; Héctor García Martín; Daniel C. Berrios; Jaden J. A. Hastings; Jon Rask; Graham Mackintosh; Adrienne L. Hoarfrost; Stuart J. Chalk; John Kalantari; et al. (CoRR, 2021)

Population-scale identification of differential adverse events before and during a pandemic. - Xiang Zhang 012; Marissa Sumathipala; Marinka Zitnik (Nat. Comput. Sci., 2021)

Contrastive learning improves critical event prediction in COVID-19 patients. - Tingyi Wanyan; Hossein Honarvar; Suraj K. Jaladanki; Chengxi Zang; Nidhi Naik; Sulaiman Somani; Jessica K. De Freitas; Ishan Paranjpe; Akhil Vaid; Jing Zhang; Riccardo Miotto; Zhangyang Wang; et al. (Patterns, 2021)

Guest Editorial: AI for COVID-19. - Yuxiao Dong; Marinka Zitnik (IEEE Trans. Big Data, 2021)

Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods. - Chirag Agarwal; Marinka Zitnik; Himabindu Lakkaraju (AISTATS, 2022)

Graph-Guided Network for Irregularly Sampled Multivariate Time Series. - Xiang Zhang 012; Marko Zeman; Theodoros Tsiligkaridis; Marinka Zitnik (ICLR, 2022)

OpenXAI: Towards a Transparent Evaluation of Model Explanations. - Chirag Agarwal; Satyapriya Krishna; Eshika Saxena; Martin Pawelczyk; Nari Johnson; Isha Puri; Marinka Zitnik; Himabindu Lakkaraju (NeurIPS, 2022)

Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency. - Xiang Zhang 012; Ziyuan Zhao; Theodoros Tsiligkaridis; Marinka Zitnik (NeurIPS, 2022)

A manifesto on explainability for artificial intelligence in medicine. - Carlo Combi; Beatrice Amico; Riccardo Bellazzi; Andreas Holzinger; Jason H. Moore; Marinka Zitnik; John H. Holmes (Artif. Intell. Medicine, 2022)

Rethinking Stability for Attribution-based Explanations. - Chirag Agarwal; Nari Johnson; Martin Pawelczyk; Satyapriya Krishna; Eshika Saxena; Marinka Zitnik; Himabindu Lakkaraju (CoRR, 2022)

Evaluating Explainability for Graph Neural Networks. - Chirag Agarwal; Owen Queen; Himabindu Lakkaraju; Marinka Zitnik (CoRR, 2022)

Geometric multimodal representation learning. - Yasha Ektefaie; George Dasoulas; Ayush Noori; Maha R. Farhat; Marinka Zitnik (CoRR, 2022)

Editorial Deep Learning and Graph Embeddings for Network Biology. - Pietro Hiram Guzzi; Marinka Zitnik (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

GNNDelete: A General Strategy for Unlearning in Graph Neural Networks. - Jiali Cheng; George Dasoulas; Huan He; Chirag Agarwal; Marinka Zitnik (ICLR, 2023)

Domain Adaptation for Time Series Under Feature and Label Shifts. - Huan He; Owen Queen; Teddy Koker; Consuelo Cuevas; Theodoros Tsiligkaridis; Marinka Zitnik (ICML, 2023)

The 3rd Workshop on Graph Learning Benchmarks (GLB 2023). - Jiaqi Ma 001; Jiong Zhu; Yuxiao Dong; Danai Koutra; Jingrui He; Qiaozhu Mei; Anton Tsitsulin; Xingjian Zhang 002; Marinka Zitnik (KDD, 2023)

Learning Generalized Medical Image Representations Through Image-Graph Contrastive Pretraining. - Sameer Tajdin Khanna; Daniel Michael; Marinka Zitnik; Pranav Rajpurkar (ML4H@NeurIPS, 2023)

Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency. - Owen Queen; Tom Hartvigsen; Teddy Koker; Huan He; Theodoros Tsiligkaridis; Marinka Zitnik (NeurIPS, 2023)

Full-Atom Protein Pocket Design via Iterative Refinement. - Zaixi Zhang; Zepu Lu; Zhongkai Hao; Marinka Zitnik; Qi Liu 003 (NeurIPS, 2023)

Graph AI in Medicine. - Ruth Johnson; Michelle M. Li; Ayush Noori; Owen Queen; Marinka Zitnik (CoRR, 2023)

Is Ignorance Bliss? The Role of Post Hoc Explanation Faithfulness and Alignment in Model Trust in Laypeople and Domain Experts. - Tessa Han; Yasha Ektefaie; Maha R. Farhat; Marinka Zitnik; Himabindu Lakkaraju (CoRR, 2023)

Multimodal learning on graphs for disease relation extraction. - Yucong Lin; Keming Lu; Sheng Yu 002; Tianxi Cai; Marinka Zitnik (J. Biomed. Informatics, 2023)

Scientific discovery in the age of artificial intelligence. - Hanchen Wang 002; Tianfan Fu; Yuanqi Du; Wenhao Gao 001; Kexin Huang; Ziming Liu; Payal Chandak; Shengchao Liu; Peter Van Katwyk; Andreea Deac; Anima Anandkumar; Karianne Bergen; et al. (Nat., 2023)

Extending the Nested Model for User-Centric XAI: A Design Study on GNN-based Drug Repurposing. - Qianwen Wang; Kexin Huang; Payal Chandak; Marinka Zitnik; Nils Gehlenborg (IEEE Trans. Vis. Comput. Graph., 2023)

Multimodal representation learning for predicting molecule-disease relations. - Jun Wen; Xiang Zhang 012; Everett Neil Rush; Vidul Ayakulangara Panickan; Xingyu Li; Tianrun Cai; Doudou Zhou; Yuk-Lam Ho; Lauren Costa; Edmon Begoli; Chuan Hong; J. Michael Gaziano; et al. (Bioinform., 2023)

Biological research and self-driving labs in deep space supported by artificial intelligence. - Lauren M. Sanders; Ryan T. Scott; Jason H. Yang; Amina Ann Qutub; Héctor García Martín; Daniel C. Berrios; Jaden J. A. Hastings; Jon Rask; Graham Mackintosh; Adrienne L. Hoarfrost; Stuart J. Chalk; John Kalantari; et al. (Nat. Mac. Intell., 2023)

Biomonitoring and precision health in deep space supported by artificial intelligence. - Ryan T. Scott; Lauren M. Sanders; Erik L. Antonsen; Jaden J. A. Hastings; Seung-Min Park; Graham Mackintosh; Robert J. Reynolds; Adrienne L. Hoarfrost; Aenor Sawyer; Casey S. Greene; Benjamin S. Glicksberg; Corey A. Theriot; et al. (Nat. Mac. Intell., 2023)

Multimodal learning with graphs. - Yasha Ektefaie; George Dasoulas; Ayush Noori; Maha R. Farhat; Marinka Zitnik (Nat. Mac. Intell., 2023)

Metapaths: similarity search in heterogeneous knowledge graphs via meta-paths. - Ayush Noori; Michelle M. Li; Amelia L. M. Tan; Marinka Zitnik (Bioinform., 2023)

Structure-inducing pre-training. - Matthew B. A. McDermott; Brendan Yap; Peter Szolovits; Marinka Zitnik (Nat. Mac. Intell., 2023)

MoExtend: Tuning New Experts for Modality and Task Extension. - Shanshan Zhong; Shanghua Gao; Zhongzhan Huang; Wushao Wen; Marinka Zitnik; Pan Zhou 002 (ACL (Student Research Workshop), 2024)

Let's Think Outside the Box: Exploring Leap-of-Thought in Large Language Models with Creative Humor Generation. - Shanshan Zhong; Zhongzhan Huang; Shanghua Gao; Wushao Wen; Liang Lin; Marinka Zitnik; Pan Zhou 002 (CVPR, 2024)

Position: TrustLLM: Trustworthiness in Large Language Models. - Yue Huang; Lichao Sun 001; Haoran Wang 005; Siyuan Wu 001; Qihui Zhang; Yuan Li; Chujie Gao; Yixin Huang; Wenhan Lyu; Yixuan Zhang; Xiner Li; Hanchi Sun; et al. (ICML, 2024)

Graph Adversarial Diffusion Convolution. - Songtao Liu; Jinghui Chen; Tianfan Fu; Lu Lin 001; Marinka Zitnik; Dinghao Wu (ICML, 2024)

UniTS: A Unified Multi-Task Time Series Model. - Shanghua Gao; Teddy Koker; Owen Queen; Tom Hartvigsen; Theodoros Tsiligkaridis; Marinka Zitnik (NeurIPS, 2024)

Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation. - Keqiang Yan; Xiner Li; Hongyi Ling; Kenna Ashen; Carl Edwards; Raymundo Arróyave; Marinka Zitnik; Heng Ji 001; Xiaofeng Qian; Xiaoning Qian; Shuiwang Ji (NeurIPS, 2024)

Generalized Protein Pocket Generation with Prior-Informed Flow Matching. - Zaixi Zhang; Marinka Zitnik; Qi Liu 003 (NeurIPS, 2024)

TrustLLM: Trustworthiness in Large Language Models. - Lichao Sun 001; Yue Huang 001; Haoran Wang 005; Siyuan Wu 001; Qihui Zhang; Chujie Gao; Yixin Huang; Wenhan Lyu; Yixuan Zhang 001; Xiner Li; Zhengliang Liu; Yixin Liu 002; et al. (CoRR, 2024)

UniTS: Building a Unified Time Series Model. - Shanghua Gao; Teddy Koker; Owen Queen; Thomas Hartvigsen; Theodoros Tsiligkaridis; Marinka Zitnik (CoRR, 2024)

Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. - Hyewon Jeong; Sarah Jabbour; Yuzhe Yang 003; Rahul Thapa; Hussein Mozannar; William Jongwon Han; Nikita Mehandru; Michael Wornow; Vladislav Lialin; Xin Liu 034; Alejandro Lozano; Jiacheng Zhu; et al. (CoRR, 2024)

Empowering Biomedical Discovery with AI Agents. - Shanghua Gao; Ada Fang; Yepeng Huang; Valentina Giunchiglia; Ayush Noori; Jonathan Richard Schwarz; Yasha Ektefaie; Jovana Kondic; Marinka Zitnik (CoRR, 2024)

Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate? - Kangyu Zheng; Yingzhou Lu; Zaixi Zhang; Zhongwei Wan; Yao Ma; Marinka Zitnik; Tianfan Fu (CoRR, 2024)

TrialBench: Multi-Modal Artificial Intelligence-Ready Clinical Trial Datasets. - Jintai Chen; Yaojun Hu; Yue Wang; Yingzhou Lu; Xu Cao; Miao Lin; Hongxia Xu; Jian Wu 001; Cao Xiao; Jimeng Sun 001; Lucas Glass; Kexin Huang; et al. (CoRR, 2024)

Quantum-machine-assisted Drug Discovery: Survey and Perspective. - Yidong Zhou; Jintai Chen; Jinglei Cheng; Gopal Karemore; Marinka Zitnik; Frederic T. Chong; Junyu Liu; Tianfan Fu; Zhiding Liang (CoRR, 2024)

How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities. - Charlotte Bunne; Yusuf H. Roohani; Yanay Rosen; Ankit Gupta; Xikun Zhang 001; Marcel Roed; Theo Alexandrov; Mohammed AlQuraishi; Patricia Brennan; Daniel B. Burkhardt; Andrea Califano; Jonah Cool; et al. (CoRR, 2024)

Repurposing Foundation Model for Generalizable Medical Time Series Classification. - Nan Huang 004; Haishuai Wang; Zihuai He; Marinka Zitnik; Xiang Zhang 012 (CoRR, 2024)

Knowledge Graph Based Agent for Complex, Knowledge-Intensive QA in Medicine. - Xiaorui Su 001; Yibo Wang 001; Shanghua Gao; Xiaolong Liu; Valentina Giunchiglia; Djork-Arné Clevert; Marinka Zitnik (CoRR, 2024)

FoldMark: Protecting Protein Generative Models with Watermarking. - Zaixi Zhang; Ruofan Jin; Kaidi Fu; Le Cong; Marinka Zitnik; Mengdi Wang (CoRR, 2024)

Multi Scale Graph Neural Network for Alzheimer's Disease. - Anya Chauhan; Ayush Noori; Zhaozhi Li; Yingnan He; Michelle M. Li; Marinka Zitnik; Sudeshna Das 001 (CoRR, 2024)

GNN 101: Visual Learning of Graph Neural Networks in Your Web Browser. - Yilin Lu; Chongwei Chen; Kexin Huang; Marinka Zitnik; Qianwen Wang (CoRR, 2024)

Evaluating generalizability of artificial intelligence models for molecular datasets. - Yasha Ektefaie; Andrew Shen; Daria Bykova; Maximillian G. Marin; Marinka Zitnik; Maha R. Farhat (Nat. Mac. Intell., 2024)

Anniversary AI reflections. - Noelia Ferruz; Marinka Zitnik; Pierre-Yves Oudeyer; Emmie Hine; Nandana Sengupta; Yiyu Shi 001; Diana Mincu; Sebastian Porsdam Mann; Payel Das; Francesco Stella (Nat. Mac. Intell., 2024)

Efficient generation of protein pockets with PocketGen. - Zaixi Zhang; Wan Xiang Shen; Qi Liu 003; Marinka Zitnik (Nat. Mac. Intell., 2024)

KGARevion: An AI Agent for Knowledge-Intensive Biomedical QA. - Xiaorui Su 001; Yibo Wang 001; Shanghua Gao; Xiaolong Liu; Valentina Giunchiglia; Djork-Arné Clevert; Marinka Zitnik (ICLR, 2025)

Composable Interventions for Language Models. - Arinbjörn Kolbeinsson; Kyle O'Brien; Tianjin Huang; Shanghua Gao; Shiwei Liu 003; Jonathan Richard Schwarz; Anurag Jayant Vaidya; Faisal Mahmood 001; Marinka Zitnik; Tianlong Chen 001; Thomas Hartvigsen (ICLR, 2025)

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. - Xuan Zhang; Limei Wang; Jacob Helwig; Youzhi Luo; Cong Fu 003; Yaochen Xie; Meng Liu 015; Yuchao Lin; Zhao Xu 005; Keqiang Yan; Keir Adams; Maurice Weiler; et al. (Found. Trends Mach. Learn., 2025)

Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases. - Emily Alsentzer; Michelle M. Li; Shilpa N. Kobren; Ayush Noori; Isaac S. Kohane; Marinka Zitnik (npj Digit. Medicine, 2025)

Controllable Sequence Editing for Counterfactual Generation. - Michelle M. Li; Kevin Li; Yasha Ektefaie; Shvat Messica; Marinka Zitnik (CoRR, 2025)

Multimodal Medical Code Tokenizer. - Xiao-Rui Su 001; Shvat Messica; Yepeng Huang; Ruth Johnson; Lukas Fesser; Shanghua Gao; Faryad Sahneh; Marinka Zitnik (CoRR, 2025)

Multimodal AI predicts clinical outcomes of drug combinations from preclinical data. - Yepeng Huang; Xiao-Rui Su 001; Varun Ullanat; Ivy Liang; Lindsay Clegg; Damilola Olabode; Nicholas Ho; Bino John; Megan Gibbs; Marinka Zitnik (CoRR, 2025)

TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools. - Shanghua Gao; Richard Zhu; Zhenglun Kong; Ayush Noori; Xiao-Rui Su 001; Curtis Ginder; Theodoros Tsiligkaridis; Marinka Zitnik (CoRR, 2025)

PyTDC: A multimodal machine learning training, evaluation, and inference platform for biomedical foundation models. - Alejandro Velez-Arce; Marinka Zitnik (CoRR, 2025)

Token Reduction Should Go Beyond Efficiency in Generative Models - From Vision, Language to Multimodality. - Zhenglun Kong; Yize Li; Fanhu Zeng; Lei Xin; Shvat Messica; Xue Lin; Pu Zhao; Manolis Kellis; Hao Tang; Marinka Zitnik (CoRR, 2025)

Prompting Decision Transformers for Zero-Shot Reach-Avoid Policies. - Kevin Li; Marinka Zitnik (CoRR, 2025)

A Causality-Aware Paradigm for Evaluating Creativity of Multimodal Large Language Models. - Zhongzhan Huang; Shanshan Zhong; Pan Zhou 002; Shanghua Gao; Marinka Zitnik; Liang Lin (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

One Patient, Many Contexts: Scaling Medical AI Through Contextual Intelligence. - Michelle M. Li; Ben Y. Reis; Adam Rodman; Tianxi Cai; Noa Dagan; Ran D. Balicer; Joseph Loscalzo; Isaac S. Kohane; Marinka Zitnik (CoRR, 2025)

Ken Utilization Layer: Hebbian Replay Within a Student's Ken for Adaptive Knowledge Tracing. - Grey Kuling; Marinka Zitnik (CoRR, 2025)

SPATIA: Multimodal Model for Prediction and Generation of Spatial Cell Phenotypes. - Zhenglun Kong; Mufan Qiu; John Boesen; Xiang Li 001; Sukwon Yun; Tianlong Chen 001; Manolis Kellis; Marinka Zitnik (CoRR, 2025)