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2020 – today
- 2024
[j46]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): 6-12 (2024)- [c31]Shanshan Zhong, Shanghua Gao, Zhongzhan Huang, Wushao Wen, Marinka Zitnik, Pan Zhou:
MoExtend: Tuning New Experts for Modality and Task Extension. ACL (Student Research Workshop) 2024: 80-91 - [c30]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. CVPR 2024: 13246-13257 - [c29]Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, 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, Joaquin Vanschoren, John C. 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, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024 - [c28]Songtao Liu, Jinghui Chen, Tianfan Fu, Lu Lin, Marinka Zitnik, Dinghao Wu:
Graph Adversarial Diffusion Convolution. ICML 2024 - [i60]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, 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 C. 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 abs/2401.05561 (2024) - [i59]Shanghua Gao, Teddy Koker, Owen Queen, Thomas Hartvigsen, Theodoros Tsiligkaridis, Marinka Zitnik:
UniTS: Building a Unified Time Series Model. CoRR abs/2403.00131 (2024) - [i58]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 abs/2403.01628 (2024) - [i57]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 abs/2404.02831 (2024) - [i56]Sameer Tajdin Khanna, Daniel Michael, Marinka Zitnik, Pranav Rajpurkar:
Learning Generalized Medical Image Representations through Image-Graph Contrastive Pretraining. CoRR abs/2405.09594 (2024) - [i55]Songtao Liu, Jinghui Chen, Tianfan Fu, Lu Lin, Marinka Zitnik, Dinghao Wu:
Graph Adversarial Diffusion Convolution. CoRR abs/2406.02059 (2024) - [i54]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 abs/2406.03403 (2024) - [i53]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 abs/2407.00631 (2024) - [i52]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 abs/2407.06483 (2024) - [i51]Shanshan Zhong, Shanghua Gao, Zhongzhan Huang, Wushao Wen, Marinka Zitnik, Pan Zhou:
MoExtend: Tuning New Experts for Modality and Task Extension. CoRR abs/2408.03511 (2024) - [i50]Yidong Zhou, Jintai Chen, Jinglei Cheng, Gopal Karemore, Marinka Zitnik, Frederic T. Chong, Junyu Liu, Tianfan Fu, Zhiding Liang:
Quantum-machine-assisted Drug Discovery: Survey and Perspective. CoRR abs/2408.13479 (2024) - [i49]Charlotte Bunne, Yusuf Roohani, Yanay Rosen, Ankit Gupta, Xikun Zhang, Marcel Roed, Theo Alexandrov, Mohammed AlQuraishi, Patricia Brennan, Daniel B. Burkhardt, Andrea Califano, Jonah Cool, Abby F. Dernburg, Kirsty Ewing, Emily B. Fox, Matthias Haury, Amy E. Herr, Eric Horvitz, Patrick D. Hsu, Viren Jain, Gregory R. Johnson, Thomas Kalil, David R. Kelley, Shana O. Kelley, Anna Kreshuk, Tim Mitchison, Stephani Otte, Jay Shendure, Nicolas J. Sofroniew, Fabian J. Theis, Christina V. Theodoris, Srigokul Upadhyayula, Marc Valer, Bo Wang, Eric Xing, Serena Yeung-Levy, Marinka Zitnik, Theofanis Karaletsos, Aviv Regev, Emma Lundberg, Jure Leskovec, Stephen R. Quake:
How to Build the Virtual Cell with Artificial Intelligence: Priorities and Opportunities. CoRR abs/2409.11654 (2024) - [i48]Nan Huang, Haishuai Wang, Zihuai He, Marinka Zitnik, Xiang Zhang:
Repurposing Foundation Model for Generalizable Medical Time Series Classification. CoRR abs/2410.03794 (2024) - [i47]Xiaorui Su, Yibo Wang, Shanghua Gao, Xiaolong Liu, Valentina Giunchiglia, Djork-Arné Clevert, Marinka Zitnik:
Knowledge Graph Based Agent for Complex, Knowledge-Intensive QA in Medicine. CoRR abs/2410.04660 (2024) - [i46]Zaixi Zhang, Ruofan Jin, Kaidi Fu, Le Cong, Marinka Zitnik, Mengdi Wang:
FoldMark: Protecting Protein Generative Models with Watermarking. CoRR abs/2410.20354 (2024) - 2023
- [j45]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) - [j44]Ayush Noori, Michelle M. Li, Amelia L. M. Tan, Marinka Zitnik:
Metapaths: similarity search in heterogeneous knowledge graphs via meta-paths. Bioinform. 39(5) (2023) - [j43]Yucong Lin, Keming Lu, Sheng Yu, Tianxi Cai, Marinka Zitnik:
Multimodal learning on graphs for disease relation extraction. J. Biomed. Informatics 143: 104415 (2023) - [j42]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 A. 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): 196-207 (2023) - [j41]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 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 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): 208-219 (2023) - [j40]Yasha Ektefaie, George Dasoulas, Ayush Noori, Maha Farhat, Marinka Zitnik:
Multimodal learning with graphs. Nat. Mac. Intell. 5(4): 340-350 (2023) - [j39]Matthew B. A. McDermott, Brendan Yap, Peter Szolovits, Marinka Zitnik:
Structure-inducing pre-training. Nat. Mac. Intell. 5(6): 612-621 (2023) - [j38]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): 47-60 (2023) - [j37]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): 1266-1276 (2023) - [c27]Jiali Cheng, George Dasoulas, Huan He, Chirag Agarwal, Marinka Zitnik:
GNNDelete: A General Strategy for Unlearning in Graph Neural Networks. ICLR 2023 - [c26]Huan He, Owen Queen, Teddy Koker, Consuelo Cuevas, Theodoros Tsiligkaridis, Marinka Zitnik:
Domain Adaptation for Time Series Under Feature and Label Shifts. ICML 2023: 12746-12774 - [c25]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: 5870-5871 - [c24]Sameer Tajdin Khanna, Daniel Michael, Marinka Zitnik, Pranav Rajpurkar:
Learning Generalized Medical Image Representations Through Image-Graph Contrastive Pretraining. ML4H@NeurIPS 2023: 232-243 - [c23]Owen Queen, Tom Hartvigsen, Teddy Koker, Huan He, Theodoros Tsiligkaridis, Marinka Zitnik:
Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency. NeurIPS 2023 - [c22]Zaixi Zhang, Zepu Lu, Zhongkai Hao, Marinka Zitnik, Qi Liu:
Full-Atom Protein Pocket Design via Iterative Refinement. NeurIPS 2023 - [i45]Huan He, Owen Queen, Teddy Koker, Consuelo Cuevas, Theodoros Tsiligkaridis, Marinka Zitnik:
Domain Adaptation for Time Series Under Feature and Label Shifts. CoRR abs/2302.03133 (2023) - [i44]Jiali Cheng, George Dasoulas, Huan He, Chirag Agarwal, Marinka Zitnik:
GNNDelete: A General Strategy for Unlearning in Graph Neural Networks. CoRR abs/2302.13406 (2023) - [i43]Owen Queen, Thomas Hartvigsen, Teddy Koker, Huan He, Theodoros Tsiligkaridis, Marinka Zitnik:
Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency. CoRR abs/2306.02109 (2023) - [i42]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 J. 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 abs/2307.08423 (2023) - [i41]Ruth Johnson, Michelle M. Li, Ayush Noori, Owen Queen, Marinka Zitnik:
Graph AI in Medicine. CoRR abs/2310.13767 (2023) - [i40]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 abs/2312.02439 (2023) - [i39]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 abs/2312.05690 (2023) - 2022
- [j36]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: 102423 (2022) - [j35]Pietro Hiram Guzzi, Marinka Zitnik:
Editorial Deep Learning and Graph Embeddings for Network Biology. IEEE ACM Trans. Comput. Biol. Bioinform. 19(2): 653-654 (2022) - [c21]Chirag Agarwal, Marinka Zitnik, Himabindu Lakkaraju:
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods. AISTATS 2022: 8969-8996 - [c20]Xiang Zhang, Marko Zeman, Theodoros Tsiligkaridis, Marinka Zitnik:
Graph-Guided Network for Irregularly Sampled Multivariate Time Series. ICLR 2022 - [c19]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 - [c18]Xiang Zhang, Ziyuan Zhao, Theodoros Tsiligkaridis, Marinka Zitnik:
Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency. NeurIPS 2022 - [i38]Chirag Agarwal, Nari Johnson, Martin Pawelczyk, Satyapriya Krishna, Eshika Saxena, Marinka Zitnik, Himabindu Lakkaraju:
Rethinking Stability for Attribution-based Explanations. CoRR abs/2203.06877 (2022) - [i37]Yucong Lin, Keming Lu, Sheng Yu, Tianxi Cai, Marinka Zitnik:
Multimodal Learning on Graphs for Disease Relation Extraction. CoRR abs/2203.08893 (2022) - [i36]Xiang Zhang, Ziyuan Zhao, Theodoros Tsiligkaridis, Marinka Zitnik:
Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency. CoRR abs/2206.08496 (2022) - [i35]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 abs/2206.11104 (2022) - [i34]Chirag Agarwal, Owen Queen, Himabindu Lakkaraju, Marinka Zitnik:
Evaluating Explainability for Graph Neural Networks. CoRR abs/2208.09339 (2022) - [i33]Yasha Ektefaie, George Dasoulas, Ayush Noori, Maha Farhat, Marinka Zitnik:
Geometric multimodal representation learning. CoRR abs/2209.03299 (2022) - 2021
- [j34]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): 5545-5547 (2021) - [j33]Xiang Zhang, Marissa Sumathipala, Marinka Zitnik:
Population-scale identification of differential adverse events before and during a pandemic. Nat. Comput. Sci. 1(10): 666-677 (2021) - [j32]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): 100389 (2021) - [j31]Yuxiao Dong, Marinka Zitnik:
Guest Editorial: AI for COVID-19. IEEE Trans. Big Data 7(1): 1-2 (2021) - [c17]Yuan Luo, Fei Wang, Marinka Zitnik, Shuiwang Ji:
Graph Based Machine Learning for Healthcare: State of the Art, Challenges, and Opportunities. AMIA 2021 - [c16]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 - [c15]Chirag Agarwal, Himabindu Lakkaraju, Marinka Zitnik:
Towards a unified framework for fair and stable graph representation learning. UAI 2021: 2114-2124 - [i32]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 abs/2101.04013 (2021) - [i31]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 abs/2102.09548 (2021) - [i30]Chirag Agarwal, Himabindu Lakkaraju, Marinka Zitnik:
Towards a Unified Framework for Fair and Stable Graph Representation Learning. CoRR abs/2102.13186 (2021) - [i29]Matthew B. A. McDermott, Brendan Yap, Peter Szolovits, Marinka Zitnik:
Rethinking Relational Encoding in Language Model: Pre-Training for General Sequences. CoRR abs/2103.10334 (2021) - [i28]Michelle M. Li, Kexin Huang, Marinka Zitnik:
Representation Learning for Networks in Biology and Medicine: Advancements, Challenges, and Opportunities. CoRR abs/2104.04883 (2021) - [i27]Michelle M. Li, Marinka Zitnik:
Deep Contextual Learners for Protein Networks. CoRR abs/2106.02246 (2021) - [i26]Chirag Agarwal, Marinka Zitnik, Himabindu Lakkaraju:
Towards a Rigorous Theoretical Analysis and Evaluation of GNN Explanations. CoRR abs/2106.09078 (2021) - [i25]Xiang Zhang, Marko Zeman, Theodoros Tsiligkaridis, Marinka Zitnik:
Graph-Guided Network for Irregularly Sampled Multivariate Time Series. CoRR abs/2110.05357 (2021) - [i24]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 J. Chalk, Guillermo M. Delgado-Aparicio, Melissa A. 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, 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 abs/2112.12554 (2021) - [i23]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, 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 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, 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 abs/2112.12582 (2021) - 2020
- [j30]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) - [c14]Weihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay S. Pande, Jure Leskovec:
Strategies for Pre-training Graph Neural Networks. ICLR 2020 - [c13]Emily Alsentzer, Samuel G. Finlayson, Michelle M. Li, Marinka Zitnik:
Subgraph Neural Networks. NeurIPS 2020 - [c12]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 - [c11]Kexin Huang, Marinka Zitnik:
Graph Meta Learning via Local Subgraphs. NeurIPS 2020 - [c10]Xiang Zhang, Marinka Zitnik:
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks. NeurIPS 2020 - [i22]Gregor Stiglic, Primoz Kocbek, Nino Fijacko, Marinka Zitnik, Katrien Verbert, Leona Cilar:
Interpretability of machine learning based prediction models in healthcare. CoRR abs/2002.08596 (2020) - [i21]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 abs/2004.07229 (2020) - [i20]Kexin Huang, Cao Xiao, Lucas Glass, Marinka Zitnik, Jimeng Sun:
SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks. CoRR abs/2004.14949 (2020) - [i19]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 abs/2005.00687 (2020) - [i18]Kexin Huang, Marinka Zitnik:
Graph Meta Learning via Local Subgraphs. CoRR abs/2006.07889 (2020) - [i17]Xiang Zhang, Marinka Zitnik:
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks. CoRR abs/2006.08149 (2020) - [i16]Emily Alsentzer, Samuel G. Finlayson, Michelle M. Li, Marinka Zitnik:
Subgraph Neural Networks. CoRR abs/2006.10538 (2020) - [i15]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 abs/2010.03951 (2020)
2010 – 2019
- 2019
- [j29]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): 1745-1752 (2019) - [j28]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: 71-91 (2019) - [c9]Zhitao Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, Jure Leskovec:
GNNExplainer: Generating Explanations for Graph Neural Networks. NeurIPS 2019: 9240-9251 - [i14]Rex Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, Jure Leskovec:
GNN Explainer: A Tool for Post-hoc Explanation of Graph Neural Networks. CoRR abs/1903.03894 (2019) - [i13]Weihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay S. Pande, Jure Leskovec:
Pre-training Graph Neural Networks. CoRR abs/1905.12265 (2019) - 2018
- [j27]Marinka Zitnik, Monica Agrawal, Jure Leskovec:
Modeling polypharmacy side effects with graph convolutional networks. Bioinform. 34(13): i457-i466 (2018) - [c8]Claire Donnat, Marinka Zitnik, David Hallac, Jure Leskovec:
Learning Structural Node Embeddings via Diffusion Wavelets. KDD 2018: 1320-1329 - [c7]William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec:
Embedding Logical Queries on Knowledge Graphs. NeurIPS 2018: 2030-2041 - [c6]Monica Agrawal, Marinka Zitnik, Jure Leskovec:
Large-scale analysis of disease pathways in the human interactome. PSB 2018: 111-122 - [i12]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 abs/1801.09851 (2018) - [i11]Marinka Zitnik, Monica Agrawal, Jure Leskovec:
Modeling polypharmacy side effects with graph convolutional networks. CoRR abs/1802.00543 (2018) - [i10]Marinka Zitnik, Rok Sosic, Jure Leskovec:
Prioritizing network communities. CoRR abs/1805.02411 (2018) - [i9]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 abs/1805.03327 (2018) - [i8]William L. Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec:
Querying Complex Networks in Vector Space. CoRR abs/1806.01445 (2018) - [i7]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 abs/1807.00123 (2018) - [i6]Marinka Zitnik, Blaz Zupan:
NIMFA: A Python Library for Nonnegative Matrix Factorization. CoRR abs/1808.01743 (2018) - 2017
- [j26]Andrej Copar, Marinka Zitnik, Blaz Zupan:
Scalable non-negative matrix tri-factorization. BioData Min. 10(1): 41:1-41:16 (2017) - [j25]Marinka Zitnik, Jure Leskovec:
Predicting multicellular function through multi-layer tissue networks. Bioinform. 33(14): i190-i198 (2017) - [e1]Yasemin Altun, Kamalika Das, Taneli Mielikäinen, Donato Malerba, Jerzy Stefanowski, Jesse Read, Marinka Zitnik, Michelangelo Ceci, Saso Dzeroski:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part III. Lecture Notes in Computer Science 10536, Springer 2017, ISBN 978-3-319-71272-7 [contents] - [i5]