Marinka Zitnik

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 102

Top Venues

Publications

Arinbjorn Kolbeinsson, Kyle O'Brien, Tianjin Huang, Shanghua Gao, Shiwei Liu, Jonathan Richard Schwarz, Anurag Vaidya, Faisal Mahmood, Marinka Zitnik, Tianlong Chen, Thomas Hartvigsen
Composable Interventions for Language Models. CoRR (2024)
Shanghua Gao, Teddy Koker, Owen Queen, Thomas Hartvigsen, Theodoros Tsiligkaridis, Marinka Zitnik
UniTS: Building a Unified Time Series Model. CoRR (2024)
Songtao Liu, Jinghui Chen, Tianfan Fu, Lu Lin, Marinka Zitnik, Dinghao Wu
Graph Adversarial Diffusion Convolution. CoRR (2024)
Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chao Zhang, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao
TrustLLM: Trustworthiness in Large Language Models. CoRR (2024)
Shanghua Gao, Ada Fang, Yepeng Huang, Valentina Giunchiglia, Ayush Noori, Jonathan Richard Schwarz, Yasha Ektefaie, Jovana Kondic, Marinka Zitnik
Empowering Biomedical Discovery with AI Agents. CoRR (2024)
Jintai Chen, Yaojun Hu, Yue Wang, Yingzhou Lu, Xu Cao, Miao Lin, Hongxia Xu, Jian Wu, Cao Xiao, Jimeng Sun, Lucas Glass, Kexin Huang, Marinka Zitnik, Tianfan Fu
TrialBench: Multi-Modal Artificial Intelligence-Ready Clinical Trial Datasets. CoRR (2024)
Sameer Tajdin Khanna, Daniel Michael, Marinka Zitnik, Pranav Rajpurkar
Learning Generalized Medical Image Representations through Image-Graph Contrastive Pretraining. CoRR (2024)
Kangyu Zheng, Yingzhou Lu, Zaixi Zhang, Zhongwei Wan, Yao Ma, Marinka Zitnik, Tianfan Fu
Structure-based Drug Design Benchmark: Do 3D Methods Really Dominate? CoRR (2024)
Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai "Orson" Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gürsoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR (2024)
Noelia Ferruz, Marinka Zitnik, Pierre-Yves Oudeyer, Emmie Hine, Nandana Sengupta, Yiyu Shi, Diana Mincu, Sebastian Porsdam Mann, Payel Das, Francesco Stella
Anniversary AI reflections. Nat. Mac. Intell. 6 (1) (2024)
Matthew B. A. McDermott, Brendan Yap, Peter Szolovits, Marinka Zitnik
Structure-inducing pre-training. Nat. Mac. Intell. 5 (6) (2023)
Jiali Cheng, George Dasoulas, Huan He, Chirag Agarwal, Marinka Zitnik
GNNDelete: A General Strategy for Unlearning in Graph Neural Networks. CoRR (2023)
Tessa Han, Yasha Ektefaie, Maha Farhat, Marinka Zitnik, Himabindu Lakkaraju
Is Ignorance Bliss? The Role of Post Hoc Explanation Faithfulness and Alignment in Model Trust in Laypeople and Domain Experts. CoRR (2023)
Zaixi Zhang, Zepu Lu, Zhongkai Hao, Marinka Zitnik, Qi Liu
Full-Atom Protein Pocket Design via Iterative Refinement. NeurIPS (2023)
Ruth Johnson, Michelle M. Li, Ayush Noori, Owen Queen, Marinka Zitnik
Graph AI in Medicine. CoRR (2023)
Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR (2023)
Hanchen Wang, Tianfan Fu, Yuanqi Du, Wenhao Gao, Kexin Huang, Ziming Liu, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomes, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora S. Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Linfeng Zhang, Connor W. Coley, Yoshua Bengio, Marinka Zitnik
Scientific discovery in the age of artificial intelligence. Nat. 620 (7972) (2023)
Ayush Noori, Michelle M. Li, Amelia L. M. Tan, Marinka Zitnik
: similarity search in heterogeneous knowledge graphs via meta-paths. Bioinform. 39 (5) (2023)
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, Kia Khezeli, Erik L. Antonsen, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Guillermo M. Delgado-Aparicio, Benjamin S. Glicksberg, Casey S. Greene, Melissa Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Christopher E. Mason, Mona Matar, George I. Mias, Jack Miller, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Seung-Min Park, Patricia Parsons-Wingerter, R. K. Prabhu, Robert J. Reynolds, Amanda Saravia-Butler, Suchi Saria, Aenor Sawyer, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, Corey A. Theriot, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Marinka Zitnik, Sylvain V. Costes
Biological research and self-driving labs in deep space supported by artificial intelligence. Nat. Mac. Intell. 5 (3) (2023)
Qianwen Wang, Kexin Huang, Payal Chandak, Marinka Zitnik, Nils Gehlenborg
Extending the Nested Model for User-Centric XAI: A Design Study on GNN-based Drug Repurposing. IEEE Trans. Vis. Comput. Graph. 29 (1) (2023)
Jiaqi Ma, Jiong Zhu, Yuxiao Dong, Danai Koutra, Jingrui He, Qiaozhu Mei, Anton Tsitsulin, Xingjian Zhang, Marinka Zitnik
The 3rd Workshop on Graph Learning Benchmarks (GLB 2023). KDD (2023)
Yucong Lin, Keming Lu, Sheng Yu, Tianxi Cai, Marinka Zitnik
Multimodal learning on graphs for disease relation extraction. J. Biomed. Informatics 143 (2023)
Owen Queen, Tom Hartvigsen, Teddy Koker, Huan He, Theodoros Tsiligkaridis, Marinka Zitnik
Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency. NeurIPS (2023)
Huan He, Owen Queen, Teddy Koker, Consuelo Cuevas, Theodoros Tsiligkaridis, Marinka Zitnik
Domain Adaptation for Time Series Under Feature and Label Shifts. CoRR (2023)
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, Daniel C. Berrios, Jack Miller, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Stuart J. Chalk, Guillermo M. Delgado-Aparicio, Melissa Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, John Kalantari, Kia Khezeli, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Héctor García Martín, Christopher E. Mason, Mona Matar, George I. Mias, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Patricia Parsons-Wingerter, R. K. Prabhu, Amina Ann Qutub, Jon Rask, Amanda Saravia-Butler, Suchi Saria, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Jason H. Yang, Marinka Zitnik, Sylvain V. Costes
Biomonitoring and precision health in deep space supported by artificial intelligence. Nat. Mac. Intell. 5 (3) (2023)
Owen Queen, Thomas Hartvigsen, Teddy Koker, Huan He, Theodoros Tsiligkaridis, Marinka Zitnik
Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency. CoRR (2023)
Sameer Tajdin Khanna, Daniel Michael, Marinka Zitnik, Pranav Rajpurkar
Learning Generalized Medical Image Representations Through Image-Graph Contrastive Pretraining. ML4H@NeurIPS (2023)
Huan He, Owen Queen, Teddy Koker, Consuelo Cuevas, Theodoros Tsiligkaridis, Marinka Zitnik
Domain Adaptation for Time Series Under Feature and Label Shifts. ICML (2023)
Yasha Ektefaie, George Dasoulas, Ayush Noori, Maha Farhat, Marinka Zitnik
Multimodal learning with graphs. Nat. Mac. Intell. 5 (4) (2023)
Jun Wen, Xiang Zhang, Everett Neil Rush, Vidul Ayakulangara Panickan, Xingyu Li, Tianrun Cai, Doudou Zhou, Yuk-Lam Ho, Lauren Costa, Edmon Begoli, Chuan Hong, J. Michael Gaziano, Kelly Cho, Junwei Lu, Katherine P. Liao, Marinka Zitnik, Tianxi Cai
Multimodal representation learning for predicting molecule-disease relations. Bioinform. 39 (2) (2023)
Shanshan Zhong, Zhongzhan Huang, Shanghua Gao, Wushao Wen, Liang Lin, Marinka Zitnik, Pan Zhou
Let's Think Outside the Box: Exploring Leap-of-Thought in Large Language Models with Creative Humor Generation. CoRR (2023)
Jiali Cheng, George Dasoulas, Huan He, Chirag Agarwal, Marinka Zitnik
GNNDelete: A General Strategy for Unlearning in Graph Neural Networks. ICLR (2023)
Chirag Agarwal, Marinka Zitnik, Himabindu Lakkaraju
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods. AISTATS (2022)
Xiang Zhang, Marko Zeman, Theodoros Tsiligkaridis, Marinka Zitnik
Graph-Guided Network for Irregularly Sampled Multivariate Time Series. ICLR (2022)
Chirag Agarwal, Eshika Saxena, Satyapriya Krishna, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, Himabindu Lakkaraju
OpenXAI: Towards a Transparent Evaluation of Model Explanations. CoRR (2022)
Xiang Zhang, Ziyuan Zhao, Theodoros Tsiligkaridis, Marinka Zitnik
Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency. CoRR (2022)
Yasha Ektefaie, George Dasoulas, Ayush Noori, Maha Farhat, Marinka Zitnik
Geometric multimodal representation learning. CoRR (2022)
Yucong Lin, Keming Lu, Sheng Yu, Tianxi Cai, Marinka Zitnik
Multimodal Learning on Graphs for Disease Relation Extraction. CoRR (2022)
Chirag Agarwal, Satyapriya Krishna, Eshika Saxena, Martin Pawelczyk, Nari Johnson, Isha Puri, Marinka Zitnik, Himabindu Lakkaraju
OpenXAI: Towards a Transparent Evaluation of Model Explanations. NeurIPS (2022)
Chirag Agarwal, Nari Johnson, Martin Pawelczyk, Satyapriya Krishna, Eshika Saxena, Marinka Zitnik, Himabindu Lakkaraju
Rethinking Stability for Attribution-based Explanations. CoRR (2022)
Chirag Agarwal, Owen Queen, Himabindu Lakkaraju, Marinka Zitnik
Evaluating Explainability for Graph Neural Networks. CoRR (2022)
Xiang Zhang, Ziyuan Zhao, Theodoros Tsiligkaridis, Marinka Zitnik
Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency. NeurIPS (2022)
Carlo Combi, Beatrice Amico, Riccardo Bellazzi, Andreas Holzinger, Jason H. Moore, Marinka Zitnik, John H. Holmes
A manifesto on explainability for artificial intelligence in medicine. Artif. Intell. Medicine 133 (2022)
Pietro Hiram Guzzi, Marinka Zitnik
Editorial Deep Learning and Graph Embeddings for Network Biology. IEEE ACM Trans. Comput. Biol. Bioinform. 19 (2) (2022)
Michelle M. Li, Marinka Zitnik
Deep Contextual Learners for Protein Networks. CoRR (2021)
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, Girish N. Nadkarni, Marinka Zitnik, Ariful Azad, Fei Wang, Ying Ding, Benjamin S. Glicksberg
Contrastive learning improves critical event prediction in COVID-19 patients. Patterns 2 (12) (2021)
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, Ariful Azad, Fei Wang, Ying Ding, Benjamin S. Glicksberg
Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients. CoRR (2021)
Matthew B. A. McDermott, Brendan Yap, Peter Szolovits, Marinka Zitnik
Rethinking Relational Encoding in Language Model: Pre-Training for General Sequences. CoRR (2021)
Xiang Zhang, Marko Zeman, Theodoros Tsiligkaridis, Marinka Zitnik
Graph-Guided Network for Irregularly Sampled Multivariate Time Series. CoRR (2021)
Chirag Agarwal, Himabindu Lakkaraju, Marinka Zitnik
Towards a unified framework for fair and stable graph representation learning. UAI (2021)
Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics. CoRR (2021)
Chirag Agarwal, Himabindu Lakkaraju, Marinka Zitnik
Towards a Unified Framework for Fair and Stable Graph Representation Learning. CoRR (2021)
Yuxiao Dong, Marinka Zitnik
Guest Editorial: AI for COVID-19. IEEE Trans. Big Data 7 (1) (2021)
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, Daniel C. Berrios, Jack Miller, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Stuart Chalk, Guillermo M. Delgado-Aparicio, Melissa Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, John Kalantari, Kia Khezeli, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Héctor García Martín, Christopher E. Mason, Mona Matar, George I. Mias, Jerry G. Myers Jr., Charlotte Nelson, Jonathan Oribello, Patricia Parsons-Wingerter, R. K. Prabhu, Amina Ann Qutub, Jon Rask, Amanda Saravia-Butler, Suchi Saria, Nitin Kumar Singh, Frank Soboczenski, Michael Snyder, Karthik Soman, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Jason H. Yang, Marinka Zitnik, Sylvain V. Costes
Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health. CoRR (2021)
Kexin Huang, Tianfan Fu, Lucas M. Glass, Marinka Zitnik, Cao Xiao, Jimeng Sun
DeepPurpose: a deep learning library for drug-target interaction prediction. Bioinform. 36 (22-23) (2021)
Michelle M. Li, Kexin Huang, Marinka Zitnik
Representation Learning for Networks in Biology and Medicine: Advancements, Challenges, and Opportunities. CoRR (2021)
Chirag Agarwal, Marinka Zitnik, Himabindu Lakkaraju
Towards a Rigorous Theoretical Analysis and Evaluation of GNN Explanations. CoRR (2021)
Xiang Zhang, Marissa Sumathipala, Marinka Zitnik
Population-scale identification of differential adverse events before and during a pandemic. Nat. Comput. Sci. 1 (10) (2021)
Yuan Luo, Fei Wang, Marinka Zitnik, Shuiwang Ji
Graph Based Machine Learning for Healthcare: State of the Art, Challenges, and Opportunities. AMIA (2021)
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 Chalk, John Kalantari, Kia Khezeli, Erik L. Antonsen, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Guillermo M. Delgado-Aparicio, Benjamin S. Glicksberg, Casey S. Greene, Melissa A. Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Christopher E. Mason, Mona Matar, George I. Mias, Jack Miller, Jerry G. Myers Jr., Charlotte Nelson, Jonathan Oribello, Seung-min Park, Patricia Parsons-Wingerter, R. K. Prabhu, Robert J. Reynolds, Amanda Saravia-Butler, Suchi Saria, Aenor Sawyer, Nitin Kumar Singh, Frank Soboczenski, Michael Snyder, Karthik Soman, Corey A. Theriot, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Marinka Zitnik, Sylvain V. Costes
Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs. CoRR (2021)
Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development. NeurIPS Datasets and Benchmarks (2021)
Xiang Zhang, Marinka Zitnik
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks. CoRR (2020)
Weihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay S. Pande, Jure Leskovec
Strategies for Pre-training Graph Neural Networks. ICLR (2020)
Emily Alsentzer, Samuel G. Finlayson, Michelle M. Li, Marinka Zitnik
Subgraph Neural Networks. NeurIPS (2020)
Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, Jure Leskovec
Open Graph Benchmark: Datasets for Machine Learning on Graphs. NeurIPS (2020)
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
Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19. CoRR (2020)
Kexin Huang, Tianfan Fu, Dawood Khan, Ali Abid, Ali Abdalla, Abubakar Abid, Lucas M. Glass, Marinka Zitnik, Cao Xiao, Jimeng Sun
MolDesigner: Interactive Design of Efficacious Drugs with Deep Learning. CoRR (2020)
Kexin Huang, Cao Xiao, Lucas Glass, Marinka Zitnik, Jimeng Sun
SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks. CoRR (2020)
Gregor Stiglic, Primoz Kocbek, Nino Fijacko, Marinka Zitnik, Katrien Verbert, Leona Cilar
Interpretability of machine learning-based prediction models in healthcare. WIREs Data Mining Knowl. Discov. 10 (5) (2020)
Gregor Stiglic, Primoz Kocbek, Nino Fijacko, Marinka Zitnik, Katrien Verbert, Leona Cilar
Interpretability of machine learning based prediction models in healthcare. CoRR (2020)
Kexin Huang, Marinka Zitnik
Graph Meta Learning via Local Subgraphs. NeurIPS (2020)
Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, Jure Leskovec
Open Graph Benchmark: Datasets for Machine Learning on Graphs. CoRR (2020)
Xiang Zhang, Marinka Zitnik
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks. NeurIPS (2020)
Emily Alsentzer, Samuel G. Finlayson, Michelle M. Li, Marinka Zitnik
Subgraph Neural Networks. CoRR (2020)
Kexin Huang, Marinka Zitnik
Graph Meta Learning via Local Subgraphs. CoRR (2020)
Xuan Wang, Yu Zhang, Xiang Ren, Yuhao Zhang, Marinka Zitnik, Jingbo Shang, Curtis P. Langlotz, Jiawei Han
Cross-type biomedical named entity recognition with deep multi-task learning. Bioinform. 35 (10) (2019)
Weihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay S. Pande, Jure Leskovec
Pre-training Graph Neural Networks. CoRR (2019)
Rex Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, Jure Leskovec
GNN Explainer: A Tool for Post-hoc Explanation of Graph Neural Networks. CoRR (2019)
Zhitao Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, Jure Leskovec
GNNExplainer: Generating Explanations for Graph Neural Networks. NeurIPS (2019)
Marinka Zitnik, Francis Nguyen, Bo Wang, Jure Leskovec, Anna Goldenberg, Michael M. Hoffman
Machine learning for integrating data in biology and medicine: Principles, practice, and opportunities. Inf. Fusion 50 (2019)
William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec
Querying Complex Networks in Vector Space. CoRR (2018)
Marinka Zitnik, Francis Nguyen, Bo Wang, Jure Leskovec, Anna Goldenberg, Michael M. Hoffman
Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities. CoRR (2018)
Marinka Zitnik, Blaz Zupan
NIMFA: A Python Library for Nonnegative Matrix Factorization. CoRR (2018)
Bo Wang, Armin Pourshafeie, Marinka Zitnik, Junjie Zhu, Carlos D. Bustamante, Serafim Batzoglou, Jure Leskovec
Network Enhancement: a general method to denoise weighted biological networks. CoRR (2018)
Marinka Zitnik, Monica Agrawal, Jure Leskovec
Modeling polypharmacy side effects with graph convolutional networks. CoRR (2018)
Claire Donnat, Marinka Zitnik, David Hallac, Jure Leskovec
Learning Structural Node Embeddings via Diffusion Wavelets. KDD (2018)
Marinka Zitnik, Monica Agrawal, Jure Leskovec
Modeling polypharmacy side effects with graph convolutional networks. Bioinform. 34 (13) (2018)
Marinka Zitnik, Rok Sosic, Jure Leskovec
Prioritizing network communities. CoRR (2018)
Monica Agrawal, Marinka Zitnik, Jure Leskovec
Large-scale analysis of disease pathways in the human interactome. PSB (2018)
William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec
Embedding Logical Queries on Knowledge Graphs. NeurIPS (2018)
Xuan Wang, Yu Zhang, Xiang Ren, Yuhao Zhang, Marinka Zitnik, Jingbo Shang, Curtis P. Langlotz, Jiawei Han
Cross-type Biomedical Named Entity Recognition with Deep Multi-Task Learning. CoRR (2018)
Andrej Copar, Marinka Zitnik, Blaz Zupan
Scalable non-negative matrix tri-factorization. BioData Min. 10 (1) (2017)
Claire Donnat, Marinka Zitnik, David Hallac, Jure Leskovec
Spectral Graph Wavelets for Structural Role Similarity in Networks. CoRR (2017)
Monica Agrawal, Marinka Zitnik, Jure Leskovec
Large-scale analysis of disease pathways in the human interactome. CoRR (2017)
Marinka Zitnik, Jure Leskovec
Predicting multicellular function through multi-layer tissue networks. CoRR (2017)
Marinka Zitnik, Jure Leskovec
Predicting multicellular function through multi-layer tissue networks. Bioinform. 33 (14) (2017)
Marinka Zitnik, Blaz Zupan
Jumping across biomedical contexts using compressive data fusion. CoRR (2017)
Marinka Zitnik, Blaz Zupan
Collective Pairwise Classification for Multi-Way Analysis of Disease and Drug Data. PSB (2016)
Marinka Zitnik
The Brownian wanderlust of things. XRDS 22 (3) (2016)
Martin Strazar, Marinka Zitnik, Blaz Zupan, Jernej Ule, Tomaz Curk
Orthogonal matrix factorization enables integrative analysis of multiple RNA binding proteins. Bioinform. 32 (10) (2016)

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Publication Activity (10 Years)

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Marinka Zitnik