[59] Paul Pu Liang, Terrance Liu, Anna Cai, Michal Muszynski, Ryo Ishii, Nick Allen, Randy Auerbach, David Brent, Ruslan Salakhutdinov, and Louis-Philippe Morency. Learning language and multimodal privacy-preserving markers of mood from mobile data. In ACL, 2021.
[60] Paul Pu Liang, Yiwei Lyu, Xiang Fan, Zetian Wu, Yun Cheng, Jason Wu, Leslie Yufan Chen, Peter Wu, Michelle A Lee, Yuke Zhu, et al. Multibench: Multiscale benchmarks for multimodal representation learning. In Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 1), 2021.
[61] Paul Pu Liang, Yiwei Lyu, Gunjan Chhablani, Nihal Jain, Zihao Deng, Xingbo Wang, Louis-Philippe Morency, and Ruslan Salakhutdinov. Multiviz: An analysis benchmark for visualizing and understanding multimodal models. arXiv preprint arXiv:2207.00056, 2022.
[62] Paul Pu Liang, Amir Zadeh, and Louis-Philippe Morency. Foundations and recent trends in multimodal machine learning: Principles, challenges, and open questions. arXiv preprint arXiv:2209.03430, 2022.
[63] Jana Lipkova, Richard J Chen, Bowen Chen, Ming Y Lu, Matteo Barbieri, Daniel Shao, Anurag J Vaidya, Chengkuan Chen, Luoting Zhuang, Drew FK Williamson, et al. Artificial intelligence for multimodal data integration in oncology. Cancer Cell, 40(10):1095-1110, 2022.
[64] Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. Roberta: A robustly optimized bert pretraining approach, 2019.
[65] Zhun Liu, Ying Shen, Varun Bharadhwaj Lakshminarasimhan, Paul Pu Liang, AmirAli Bagher Zadeh, and Louis-Philippe Morency. Efficient low-rank multimodal fusion with modality-specific factors. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2247–2256, 2018.
[66] David N Louis, Arie Perry, Guido Reifenberger, Andreas Von Deimling, Dominique Figarella-Branger, Webster K Cavenee, Hiroko Ohgaki, Otmar D Wiestler, Paul Kleihues, and David W Ellison. The 2016 world health organization classification of tumors of the central nervous system: a summary. Acta neuropathologica, 131(6):803–820, 2016.
[67] Scott M Lundberg and Su-In Lee. A unified approach to interpreting model predictions. Advances in neural information processing systems, 30, 2017.
[68] Yiwei Lyu, Paul Pu Liang, Zihao Deng, Ruslan Salakhutdinov, and Louis-Philippe Morency. Dime: Fine-grained interpretations of multimodal models via disentangled local explanations. AIES, 2022.
[69] Alessio Mazzetto, Dylan Sam, Andrew Park, Eli Upfal, and Stephen Bach. Semi-supervised aggregation of dependent weak supervision sources with performance guarantees. In Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, 2021.
[70] William McGill. Multivariate information transmission. Transactions of the IRE Professional Group on Information Theory, 4(4):93-111, 1954.
[71] Pooya Mobadersany, Safoora Yousefi, Mohamed Amgad, David A Gutman, Jill S Barnholtz-Sloan, José E Velázquez Vega, Daniel J Brat, and Lee AD Cooper. Predicting cancer outcomes from histology and genomics using convolutional networks. Proceedings of the National Academy of Sciences, 2018.
[72] Inbal Nahum-Shani, Shawna N Smith, Bonnie J Spring, Linda M Collins, Katie Witkiewitz, Ambuj Tewari, and Susan A Murphy. Just-in-time adaptive interventions (jitais) in mobile health: key components and design principles for ongoing health behavior support. Annals of Behavioral Medicine, 2018.
[73] Cancer Genome Atlas Research Network. Comprehensive, integrative genomic analysis of diffuse lower-grade gliomas. New England Journal of Medicine, 372(26):2481-2498, 2015.
[74] Sheila Nirenberg, Steve M Carcieri, Adam L Jacobs, and Peter E Latham. Retinal ganglion cells act largely as independent encoders. Nature, 411(6838):698-701, 2001.
[75] Brendan O'Donoghue, Eric Chu, Neal Parikh, and Stephen Boyd. Conic optimization via operator splitting and homogeneous self-dual embedding. Journal of Optimization Theory and Applications, 2016.
[76] Ari Pakman, Amin Nejatbakhsh, Dar Gilboa, Abdullah Makkeh, Luca Mazzucato, Michael Wibral, and Elad Schneidman. Estimating the unique information of continuous variables. Advances in Neural Information Processing Systems, 34:20295-20307, 2021.
[77] Liam Paninski. Estimation of entropy and mutual information. Neural computation, 2003.