Difference between revisions of "CSE 7300 Research Seminar"

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* '''Theme: AI for Health'''
 
* '''Theme: AI for Health'''
 
* '''Instructor''': [http://www.cse.wustl.edu/~lu Prof. Chenyang Lu]
 
* '''Instructor''': [http://www.cse.wustl.edu/~lu Prof. Chenyang Lu]
−
* '''Semester''': '''Spring 2024'''
+
* '''Semester''': '''Fall 2024'''
 
* '''Time''': Wednesday at 1 PM
 
* '''Time''': Wednesday at 1 PM
 
* '''Location''': McKelvey 1030
 
* '''Location''': McKelvey 1030
Line 12: Line 12:
  
 
==Presentation Schedule==
 
==Presentation Schedule==
−
=== ---Jan 24 ---===
 
−
Hangyue
 
  
−
Krishnamachari, Kiran, See-Kiong Ng, and Chuan-Sheng Foo. "Mitigating Real-World Distribution Shifts in the Fourier Domain." Transactions on Machine Learning Research (2023). [https://openreview.net/pdf?id=lu4oAq55iK]
+
=== ---Sep 11 ---===
−
 
 
−
=== ---Jan 31 ---===
 
−
Ruiqi
 
−
 
 
−
Faure, Gueter Josmy, Min-Hung Chen, and Shang-Hong Lai. "Holistic interaction transformer network for action detection." In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 3340-3350. 2023. [https://openaccess.thecvf.com/content/WACV2023/papers/Faure_Holistic_Interaction_Transformer_Network_for_Action_Detection_WACV_2023_paper.pdf]
 
−
 
 
−
=== ---Feb 07 ---===
 
−
Jizhou
 
−
 
 
−
Parikh, Harsh, Quinn Lanners, Zade Akras, Sahar F. Zafar, M. Brandon Westover, Cynthia Rudin, and Alexander Volfovsky. "Estimating Trustworthy and Safe Optimal Treatment Regimes." arXiv preprint arXiv:2310.15333 (2023). [https://arxiv.org/pdf/2310.15333.pdf]
 
−
 
 
−
=== ---Feb 14 ---===
 
−
Ben
 
−
 
 
−
M. Wornow, R. Thapa, E. Steinberg, J. A. Fries, and N. H. Shah, “EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models.” arXiv, Dec. 11, 2023. doi: 10.48550/arXiv.2307.02028.
 
−
 
 
−
L. L. Guo et al., “A Multi-Center Study on the Adaptability of a Shared Foundation Model for Electronic Health Records.” arXiv, Nov. 19, 2023. Available: http://arxiv.org/abs/2311.11483
 
−
 
 
−
=== ---Feb 21 ---===
 
−
Quan
 
−
 
 
−
Maus, N., Jones, H., Moore, J., Kusner, M. J., Bradshaw, J., & Gardner, J. (2022). Local latent space bayesian optimization over structured inputs. Advances in Neural Information Processing Systems, 35, 34505-34518. [https://proceedings.neurips.cc/paper_files/paper/2022/file/ded98d28f82342a39f371c013dfb3058-Paper-Conference.pdf]
 
−
 
 
−
=== ---Feb 28 ---===
 
 
Ziqi
 
Ziqi
  
−
Oral exam practice
+
Gawlikowski, J., Tassi, C.R.N., Ali, M. et al. A survey of uncertainty in deep neural networks. Artif Intell Rev 56 (Suppl 1), 1513–1589 (2023). [https://doi.org/10.1007/s10462-023-10562-9]
  
−
[1] Udandarao, Vishaal, et al. “COBRA: Contrastive Bi-Modal Representation Algorithm”, IJCAI (TUSION workshop) 2020. [https://arxiv.org/pdf/2005.03687.pdf]
+
=== ---Sep 18 ---===
 +
Daoyi
  
−
[2] Han Zongbo, et al. “Trusted Multi-View Classification.” International Conference on Learning Representations (ICLR). 2020. [https://openreview.net/pdf?id=OOsR8BzCnl5]
+
Hüyük, A., Wei, Q., Curth, A. and van der Schaar, M., 2024. Defining Expertise: Applications to Treatment Effect Estimation. arXiv preprint arXiv:2403.00694. [https://openreview.net/pdf?id=1YPfmglNRU]
  
−
[3] Zhenbang Wu et al. “Multimodal Patient Representation Learning with Missing Modalities and Labels”. International Conference on Learning Representations(ICLR), 2024. [https://openreview.net/pdf?id=Je5SHCKpPa]
+
=== ---Sep 25 ---===
 +
Jason
  
−
=== ---Mar 06 ---===
+
Park, C., Awadalla, A., Kohno, T., & Patel, S. (2021). Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection. In M. Ranzato, A. Beygelzimer, Y. Dauphin, P. S. Liang, & J. W. Vaughan (Eds.), Advances in Neural Information Processing Systems (Vol. 34, pp. 3043–3056).
−
Jiaming
+
[https://proceedings.neurips.cc/paper_files/paper/2021/file/17e23e50bedc63b4095e3d8204ce063b-Paper.pdf]
  
−
Zhang, Nan, Yusen Zhang, Wu Guo, Prasenjit Mitra, and Rui Zhang. "FaMeSumm: Investigating and Improving Faithfulness of Medical Summarization." In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pp. 10915-10931. 2023. [https://aclanthology.org/2023.emnlp-main.673/]
+
=== ---Oct 02 ---===
 +
Ben
  
−
=== ---Mar 13 ---===
+
Bick, A., Li, K.Y., Xing, E.P., Kolter, J.Z. and Gu, A., 2024. Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models. arXiv preprint arXiv:2408.10189. [https://arxiv.org/pdf/2408.10189]
−
Spring Break
 
  
−
=== ---Mar 20 ---===
+
Dao, T. and Gu, A., 2024. Transformers are SSMs: Generalized models and efficient algorithms through structured state space duality. arXiv preprint arXiv:2405.21060. [https://arxiv.org/pdf/2405.21060]
−
Charles
 
  
−
Van Veen, Dave, Cara Van Uden, Louis Blankemeier, Jean-Benoit Delbrouck, Asad Aali, Christian Bluethgen, Anuj Pareek et al. "Adapted large language models can outperform medical experts in clinical text summarization." Nature Medicine (2024): 1-9. [https://www.nature.com/articles/s41591-024-02855-5]
+
=== ---Oct 09 ---===
−
 
+
Claire
−
Liu, Nelson F., Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang. "Lost in the Middle: How Language Models Use Long Contexts." Transactions of the Association for Computational Linguistics 12 (2024). [https://watermark.silverchair.com/tacl_a_00638.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAA0YwggNCBgkqhkiG9w0BBwagggMzMIIDLwIBADCCAygGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMTsi8yvo4NZXLClG1AgEQgIIC-QP6KIRyMwLTeCSsvdL7n7VJPdpYJCGAsJSiPlCTsp-P9R6vQOcOuIPoBpjnz9D9HVBMCrXGTFbtSQmvWVmvgAfTu7VE1NUuWAjc7T4Teb_vLoW0caty8PI8NHhhRtXhzTXLC-wOFTaJKgHS3gwA3_oqoTt06gd0qpx9k_cHNP4Vw3OgxNsk39Wog6hdiwyHSuAZ712xY2sBX4jOSby0gjy87KpHWahepzE7zosvbtoCvxB8KbhxwBJJeI22rKoOddd7Gbk0YguJaLMGGRQ7jARou-smLx6v85j3hXMNd__daTr9o7keU_051aiZogDovfrEwqXc7TxMu0XHsVqjot8n16cwun61Y-V5-ll8Ov7wywFcZ9Zt5YWcsSMpx0Zmm7fjz-ocfc1mg_v6ge3HT7uWljVzqP-olpG7CxZbZMjv_sRuV8uaFM78BCrIltCcKNkZSZchckk-BT07vSYTltFcPVx6XpA0g77m2Pnd-Anu-yU8f0PTqyBxGJEw2B0FE5Oo1xGhj8RjcaM0GsA41t5miGQk_WqRdiM8M04dSyc3WG0LZwNaCNT6NVn8tqWMHu1ZaYhY2_FfsYuCEKBvQ7FMsuNym0Qhgc9TKtO3IWj8-3Hod17xvLSuC1xgR4vI07elBv20eFyhQVEmfqCQugfEEpVIVp_zJLZRJDazZrzrm-PbTkDyGjQV7Wc1-Yq_ObsJbScuGxAvi0hprJxftxj6GkGMWVfX9LyZQy6R0v6nsuz8GWYo1fVMeP6j2Y7BjT65igxFbIdS4WCo7foMJbp_0giJIqsTBw5Ai4QqHQqHgJdNwdKB6NkE1B5aJoKYF1_fh4FW8t_0dDo1tbG_TctAMRRqsYcPAjIZfncmxxgOwqWFEg5p1tpT84a-MOFesnvtK1mb2rOaWtcRRL0OnQv83QMVNJMZpF6lylIjGa7LRcRPh5G_JsljtEHSgzMUIkfSs-U0Rx4Wa7xRAd_Mi7cIbKiY_R1V4VawRr40U2LvQ3OHr4Cj3yLe]
 
  
−
=== ---Mar 27 ---===
+
Qian Z, Zhang Y, Bica I, Wood A, van der Schaar M. Synctwin: Treatment effect estimation with longitudinal outcomes. Advances in Neural Information Processing Systems. 2021 Dec 6;34:3178-90. [https://proceedings.neurips.cc/paper_files/paper/2021/file/19485224d128528da1602ca47383f078-Paper.pdf]
−
Jingwen
 
  
−
Gouareb, Racha, Alban Bornet, Dimitrios Proios, Sónia Gonçalves Pereira, and Douglas Teodoro. "Detection of Patients at Risk of Multidrug-Resistant Enterobacteriaceae Infection Using Graph Neural Networks: A Retrospective Study." Health Data Science 3 (2023): 0099. [https://spj.science.org/doi/full/10.34133/hds.0099]
+
=== ---Oct 16 ---===
 +
Wenyu
  
−
=== ---Apr 03 ---===
+
Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jiang, Bill Yuchen Lin, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D. Hwang, Soumya Sanyal, Sean Welleck, Xiang Ren, Allyson Ettinger, Zaid Harchaoui, and Yejin Choi. 2024. Faith and fate: limits of transformers on compositionality. In Proceedings of the 37th International Conference on Neural Information Processing Systems (NIPS '23). Curran Associates Inc., Red Hook, NY, USA, Article 3081, 70293–70332.
−
Hanyang
+
[https://dl.acm.org/doi/10.5555/3666122.3669203]
  
−
Jin, Ming, et al. "Time-llm: Time series forecasting by reprogramming large language models." ICLR 2024.
+
=== ---Oct 23 ---===
 +
Di
  
−
=== ---Apr 10 ---===
+
=== ---Oct 30 ---===
−
Zebo
+
Behrooz
  
−
Lockwood, Owen, and Mei Si. "Reinforcement learning with quantum variational circuit." In Proceedings of the AAAI conference on artificial intelligence and interactive digital entertainment, vol. 16, no. 1, pp. 245-251. 2020. [https://ojs.aaai.org/index.php/AIIDE/article/view/7437]
+
=== ---Nov 06 ---===
 +
Prince
  
−
=== ---Apr 17 ---===
+
=== ---Nov 13 ---===
−
Claire
+
Zichen
  
−
Prerna Chikersal, Afsaneh Doryab, Michael Tumminia, Daniella K. Villalba, Janine M. Dutcher, Xinwen Liu, Sheldon Cohen, Kasey G. Creswell, Jennifer Mankoff, J. David Creswell, Mayank Goel, and Anind K. Dey. 2021. Detecting Depression and Predicting its Onset Using Longitudinal Symptoms Captured by Passive Sensing: A Machine Learning Approach With Robust Feature Selection. ACM Trans. Comput.-Hum. Interact. 28, 1, Article 3 (February 2021), 41 pages. [https://doi.org/10.1145/3422821.]
+
=== ---Nov 20 ---===
 +
Peiqi
  
−
=== ---Apr 24 ---===
+
=== ---Nov 27 ---===
−
Daoyi
+
Thanksgiving
  
  
 
==Previous Semesters==
 
==Previous Semesters==
 +
* [[Seminar Spring 2024|Spring 2024]]
 
* [[Seminar Fall 2023|Fall 2023]]
 
* [[Seminar Fall 2023|Fall 2023]]
 
* [[Seminar Spring 2023|Spring 2023]]
 
* [[Seminar Spring 2023|Spring 2023]]

Revision as of 22:51, 12 October 2024

  • Theme: AI for Health
  • Instructor: Prof. Chenyang Lu
  • Semester: Fall 2024
  • Time: Wednesday at 1 PM
  • Location: McKelvey 1030
  • Guidelines:
  • Recommended sources: NeurIPS ([1]), ICML ([2]), AAAI ([3]), SIGKDD ([4]), IJCAI ([5]), IMWUT ([6]), HEALTH ([7]), Digital Medicine ([8]), Lancet Digital Health ([9]), NEJM AI ([10])

Presentation Schedule

---Sep 11 ---

Ziqi

Gawlikowski, J., Tassi, C.R.N., Ali, M. et al. A survey of uncertainty in deep neural networks. Artif Intell Rev 56 (Suppl 1), 1513–1589 (2023). [11]

---Sep 18 ---

Daoyi

Hüyük, A., Wei, Q., Curth, A. and van der Schaar, M., 2024. Defining Expertise: Applications to Treatment Effect Estimation. arXiv preprint arXiv:2403.00694. [12]

---Sep 25 ---

Jason

Park, C., Awadalla, A., Kohno, T., & Patel, S. (2021). Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection. In M. Ranzato, A. Beygelzimer, Y. Dauphin, P. S. Liang, & J. W. Vaughan (Eds.), Advances in Neural Information Processing Systems (Vol. 34, pp. 3043–3056). [13]

---Oct 02 ---

Ben

Bick, A., Li, K.Y., Xing, E.P., Kolter, J.Z. and Gu, A., 2024. Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models. arXiv preprint arXiv:2408.10189. [14]

Dao, T. and Gu, A., 2024. Transformers are SSMs: Generalized models and efficient algorithms through structured state space duality. arXiv preprint arXiv:2405.21060. [15]

---Oct 09 ---

Claire

Qian Z, Zhang Y, Bica I, Wood A, van der Schaar M. Synctwin: Treatment effect estimation with longitudinal outcomes. Advances in Neural Information Processing Systems. 2021 Dec 6;34:3178-90. [16]

---Oct 16 ---

Wenyu

Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jiang, Bill Yuchen Lin, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D. Hwang, Soumya Sanyal, Sean Welleck, Xiang Ren, Allyson Ettinger, Zaid Harchaoui, and Yejin Choi. 2024. Faith and fate: limits of transformers on compositionality. In Proceedings of the 37th International Conference on Neural Information Processing Systems (NIPS '23). Curran Associates Inc., Red Hook, NY, USA, Article 3081, 70293–70332. [17]

---Oct 23 ---

Di

---Oct 30 ---

Behrooz

---Nov 06 ---

Prince

---Nov 13 ---

Zichen

---Nov 20 ---

Peiqi

---Nov 27 ---

Thanksgiving


Previous Semesters

Previous Lab Meetings

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