Difference between revisions of "Seminar Spring 2024"

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(Created page with "{| align="right" | __TOC__ |} * '''Theme: AI and IoT for Medicine (AIM)''' * '''Instructor''': [http://www.cse.wustl.edu/~lu Prof. Chenyang Lu] * '''Semester''': '''Fall 20...")
 
 
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* '''Theme: AI and IoT for Medicine (AIM)'''
+
* '''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''': '''Fall 2023'''
+
* '''Semester''': '''Spring 2024'''
−
* '''Time''': Wednesday at 11am-12pm
+
* '''Time''': Wednesday at 1 PM
 
* '''Location''': McKelvey 1030
 
* '''Location''': McKelvey 1030
 
* '''[http://www.cse.wustl.edu/~lu/talks/seminar_guidelines.pdf Guidelines]''':  
 
* '''[http://www.cse.wustl.edu/~lu/talks/seminar_guidelines.pdf Guidelines]''':  
−
* '''Recommended sources:''' NeurIPS ([http://nips.cc/]), ICML ([http://icml.cc/]), AAAI ([http://www.aaai.org/]), SIGKDD ([http://www.kdd.org/]), IJCAI ([http://www.ijcai.org/]), IMWUT ([http://dl.acm.org/journal/imwut]), HEALTH ([http://dl.acm.org/journal/health]), Digital Medicine ([http://www.nature.com/npjdigitalmed/]), Lancet Digital Health ([https://www.thelancet.com/journals/landig/issues#decade=loi_decade_201]), SenSys, MobiSys, MobiCom
+
* '''Recommended sources:''' NeurIPS ([http://nips.cc/]), ICML ([http://icml.cc/]), AAAI ([http://www.aaai.org/]), SIGKDD ([http://www.kdd.org/]), IJCAI ([http://www.ijcai.org/]), IMWUT ([http://dl.acm.org/journal/imwut]), HEALTH ([http://dl.acm.org/journal/health]), Digital Medicine ([http://www.nature.com/npjdigitalmed/]), Lancet Digital Health ([https://www.thelancet.com/journals/landig/issues#decade=loi_decade_201]), NEJM AI ([https://ai.nejm.org/])
  
 
==Presentation Schedule==
 
==Presentation Schedule==
−
=== ---Sep 06 ---===
+
=== ---Jan 24 ---===
 
Hangyue
 
Hangyue
  
−
Letzgus, Simon, Patrick Wagner, Jonas Lederer, Wojciech Samek, Klaus-Robert Müller, and Gregoire Montavon. "Toward explainable artificial intelligence for regression models: A methodological perspective." IEEE Signal Processing Magazine 39, no. 4 (2022): 40-58. [https://ieeexplore.ieee.org/abstract/document/9810062]
+
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 13 ---===
+
=== ---Jan 31 ---===
 
Ruiqi
 
Ruiqi
  
−
Gupta, Akshita, Sanath Narayan, K. J. Joseph, Salman Khan, Fahad Shahbaz Khan, and Mubarak Shah. "Ow-detr: Open-world detection transformer." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 9235-9244. 2022. [https://openaccess.thecvf.com/content/CVPR2022/html/Gupta_OW-DETR_Open-World_Detection_Transformer_CVPR_2022_paper]
+
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]
  
−
=== ---Sep 20 ---===
+
=== ---Feb 07 ---===
−
Jingwen
+
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.
  
−
Dissertation Proposal Practice Talk
+
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
  
−
=== ---Sep 27 ---===
+
=== ---Feb 21 ---===
−
Bing
+
Quan
  
−
Li, Xiang Lisa, and Percy Liang. "Prefix-tuning: Optimizing continuous prompts for generation." arXiv preprint arXiv:2101.00190 (2021). [https://aclanthology.org/2021.acl-long.353.pdf]
+
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]
  
−
=== ---Oct 04 ---===
+
=== ---Feb 28 ---===
 
Ziqi
 
Ziqi
  
−
Li, Y., Hu, P., Liu, Z., Peng, D., Zhou, J. T., & Peng, X. "Contrastive Clustering." Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 10, 2021, pp. 8547-8555. [https://arxiv.org/pdf/2009.09687.pdf]
+
Oral exam practice
 +
 
 +
[1] Udandarao, Vishaal, et al. “COBRA: Contrastive Bi-Modal Representation Algorithm”, IJCAI (TUSION workshop) 2020. [https://arxiv.org/pdf/2005.03687.pdf]
  
−
=== ---Oct 11 ---===
+
[2] Han Zongbo, et al. “Trusted Multi-View Classification.” International Conference on Learning Representations (ICLR). 2020. [https://openreview.net/pdf?id=OOsR8BzCnl5]
−
Ben
 
  
−
Mao, H., Liu, H., Dou, J. X., & Benos, P. V. (2022, November). Towards cross-modal causal structure and representation learning. In Machine Learning for Health (pp. 120-140). PMLR. [https://proceedings.mlr.press/v193/mao22a/mao22a.pdf]
+
[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]
  
−
=== ---Oct 18 ---===
+
=== ---Mar 06 ---===
−
Cancelled
+
Jiaming
  
−
=== ---Oct 25 ---===
+
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/]
−
Daoyi
 
  
−
Ravindra, N. G., Espinosa, C., Berson, E., Phongpreecha, T., Zhao, P., Becker, M., ... & Aghaeepour, N. (2023). Deep representation learning identifies associations between physical activity and sleep patterns during pregnancy and prematurity. NPJ Digital Medicine, 6(1), 171. [https://www.nature.com/articles/s41746-023-00911-x]
+
=== ---Mar 13 ---===
 +
Spring Break
  
−
=== ---Nov 01 ---===
+
=== ---Mar 20 ---===
 
Charles
 
Charles
  
−
Liu, H., Tam, D., Muqeeth, M., Mohta, J., Huang, T., Bansal, M., & Raffel, C. A. (2022). Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning. Advances in Neural Information Processing Systems, 35, 1950-1965. [https://proceedings.neurips.cc/paper_files/paper/2022/file/0cde695b83bd186c1fd456302888454c-Paper-Conference.pdf]
+
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]
 +
 
 +
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 ---===
 +
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]
 +
 
 +
=== ---Apr 03 ---===
 +
Hanyang
  
−
Hu, E. J. . yelong shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. (2022) LoRA: Low-rank adaptation of large language models. In International Conference on Learning Representations (Vol. 3, p. 7).
+
Jin, Ming, et al. "Time-llm: Time series forecasting by reprogramming large language models." ICLR 2024.
−
https://arxiv.org/pdf/2106.09685.pdf
 
  
−
=== ---Nov 08 ---===
+
=== ---Apr 10 ---===
−
Jiaming
+
Zebo
  
−
Ghosh, Anurag, et al. "REACT: Streaming Video Analytics On The Edge With Asynchronous Cloud Support." Proceedings of the 8th ACM/IEEE Conference on Internet of Things Design and Implementation. 2023. [https://dl.acm.org/doi/pdf/10.1145/3576842.3582385]
+
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 15 ---===
+
=== ---Apr 17 ---===
 
Claire
 
Claire
  
−
Brathwaite, R., Ssewamala, F. M., Neilands, T. B., Okumu, M., Mutumba, M., Damulira, C., ... & McKay, M. M. (2021). Predicting the individualized risk of poor adherence to ART medication among adolescents living with HIV in Uganda: the Suubi+ Adherence study. African Journal of Reproduction and Gynaecological Endoscopy, 24(6), e25756. [https://onlinelibrary.wiley.com/share/FWHDDNGXEJQXVBFXJ78D?target=10.1002/jia2.25756]
+
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 22 ---===
+
=== ---Apr 24 ---===
−
Thanksgiving Break
+
Daoyi
  
−
=== ---Nov 29 ---===
+
Tipirneni, Sindhu, and Chandan K. Reddy. "Self-supervised transformer for sparse and irregularly sampled multivariate clinical time-series." ACM Transactions on Knowledge Discovery from Data (TKDD) 16, no. 6 (2022): 1-17. [https://dl.acm.org/doi/10.1145/3516367]
−
Mingzhen
 
  
−
Acevedo, Andrea, Anna Merino, Laura Boldú, Angel Molina, Santiago Alférez, and José Rodellar. "A new convolutional neural network predictive model for the automatic recognition of hypogranulated neutrophils in myelodysplastic syndromes." Computers in Biology and Medicine 134 (2021): 104479. [https://www.sciencedirect.com/science/article/pii/S0010482521002730]
+
==Previous Semesters==
 +
* [[Seminar Fall 2023|Fall 2023]]
 +
* [[Seminar Spring 2023|Spring 2023]]
 +
* [[Seminar Fall 2022|Fall 2022]]
 +
* [[Seminar Summer 2022|Summer 2022]]
 +
* [[Seminar Spring 2022|Spring 2022]]
 +
* [[Seminar Fall 2021|Fall 2021]]
 +
* [[Seminar Summer 2021|Summer 2021]]
 +
* [[Seminar Spring 2021|Spring 2021]]
 +
* [[Seminar Fall 2020|Fall 2020]]
 +
* [[Seminar Summer 2020|Summer 2020]]
 +
* [[Seminar Spring 2020|Spring 2020]]
 +
* [[Seminar Fall 2019|Fall 2019]]
 +
* [[Seminar Summer 2019|Summer 2019]]
 +
* [[Seminar Spring 2019|Spring 2019]]
 +
* [[Seminar Fall 2018|Fall 2018]]
 +
* [[Seminar Summer 2018|Summer 2018]]
 +
* [[Seminar Spring 2018|Spring 2018]]
 +
* [[Seminar Fall 2017|Fall 2017]]
 +
* [[Seminar Summer 2017|Summer 2017]]
 +
* [[Seminar Spring 2017|Spring 2017]]
 +
* [[Seminar Fall 2016|Fall 2016]]
 +
* [[Seminar Summer 2016|Summer 2016]]
 +
* [[Seminar Spring 2016|Spring 2016]]
 +
* [[Seminar Fall 2015|Fall 2015]]
 +
* [[Seminar Summer 2015|Summer 2015]]
 +
* [[Seminar Spring 2015|Spring 2015]]
 +
* [[Seminar Fall 2014|Fall 2014]]
 +
* [[Seminar Summer 2014|Summer 2014]]
 +
* [[Seminar Spring 2014|Spring 2014]]
 +
* [[Seminar Fall 2013|Fall 2013]]
 +
* [[Seminar Summer 2013|Summer 2013]]
 +
* [[Seminar Spring 2013|Spring 2013]]
 +
* [[Seminar Fall 2012|Fall 2012]]
 +
* [[Seminar Summer 2012|Summer 2012]]
 +
* [[Seminar Spring 2012|Spring 2012]]
 +
* [[Seminar Fall 2011|Fall 2011]]
 +
* [[Seminar Summer 2011|Summer 2011]]
 +
* [[Seminar Spring 2011|Spring 2011]]
 +
* [[Seminar Fall 2010|Fall 2010]]
 +
* [[Seminar Spring 2010|Spring 2010]]
 +
* [[Seminar Fall 2009|Fall 2009]]
 +
* [[Seminar Summer 2009|Summer 2009]]
 +
* [[Seminar Spring 2009|Spring 2009]]
 +
* [[Seminar Fall 2008|Fall 2008]]
 +
* [[Seminar Summer 2008|Summer 2008]]
 +
* [[Seminar Spring 2008|Spring 2008]]
 +
* [[Fall 2007]]
 +
* [[Summer 2007]]
 +
* [[Spring 2007]]
 +
* [[Fall 2006]]
 +
* [[Spring 2006]]
 +
* [[Fall 2005]]
 +
* [[Spring 2005]]
 +
* [[Fall 2004]]
 +
* [[Spring 2004]]
 +
* [[Fall 2003]]
 +
* [[Spring 2003]]
 +
* [[Fall 2002]]
 +
* [http://userfs.cec.wustl.edu/~cs673/spring.2002.html Spring 2002]
 +
* [http://userfs.cec.wustl.edu/~cs673/fall.2001.html Fall 2001]
 +
* [http://userfs.cec.wustl.edu/~cs673/spring.2001.html Spring 2001]
 +
* [[Fall 2000]]
 +
* [http://userfs.cec.wustl.edu/~cs673/spring.2000.html Spring 2000]
 +
* [http://cec.wustl.edu/~cs673/backUp/fall.1998.html Fall 1998]
 +
* [http://cec.wustl.edu/~cs673/backUp/spring.1998.html Spring 1998]
  
−
Lewis, Joshua E., Conrad W. Shebelut, Bradley R. Drumheller, Xuebao Zhang, Nithya Shanmugam, Michel Attieh, Michael C. Horwath et al. "An automated pipeline for differential cell counts on whole-slide bone marrow aspirate smears." Modern Pathology 36, no. 2 (2023): 100003. [https://www.sciencedirect.com/science/article/pii/S0893395222000035]
+
==Previous Lab Meetings==
 +
* [[Labmeeting Spring 2020|Spring 2020]]
 +
* [[Labmeeting Fall 2014|Fall 2014]]
 +
* [[Labmeeting Summer 2014|Summer 2014]]
 +
* [[Labmeeting Spring 2014|Spring 2014]]

Latest revision as of 15:01, 20 August 2024

  • Theme: AI for Health
  • Instructor: Prof. Chenyang Lu
  • Semester: Spring 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

---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). [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. [12]

---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). [13]

---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. [14]

---Feb 28 ---

Ziqi

Oral exam practice

[1] Udandarao, Vishaal, et al. “COBRA: Contrastive Bi-Modal Representation Algorithm”, IJCAI (TUSION workshop) 2020. [15]

[2] Han Zongbo, et al. “Trusted Multi-View Classification.” International Conference on Learning Representations (ICLR). 2020. [16]

[3] Zhenbang Wu et al. “Multimodal Patient Representation Learning with Missing Modalities and Labels”. International Conference on Learning Representations(ICLR), 2024. [17]

---Mar 06 ---

Jiaming

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. [18]

---Mar 13 ---

Spring Break

---Mar 20 ---

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. [19]

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). [20]

---Mar 27 ---

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. [21]

---Apr 03 ---

Hanyang

Jin, Ming, et al. "Time-llm: Time series forecasting by reprogramming large language models." ICLR 2024.

---Apr 10 ---

Zebo

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. [22]

---Apr 17 ---

Claire

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. [23]

---Apr 24 ---

Daoyi

Tipirneni, Sindhu, and Chandan K. Reddy. "Self-supervised transformer for sparse and irregularly sampled multivariate clinical time-series." ACM Transactions on Knowledge Discovery from Data (TKDD) 16, no. 6 (2022): 1-17. [24]

Previous Semesters

Previous Lab Meetings

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