default search action
Thomas Hartvigsen
Tom Hartvigsen
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [j2]Ramesh Doddaiah, Prathyush S. Parvatharaju, Elke A. Rundensteiner, Thomas Hartvigsen:
Explaining deep multi-class time series classifiers. Knowl. Inf. Syst. 66(6): 3497-3521 (2024) - [c38]Derek Powell, Walter Gerych, Thomas Hartvigsen
:
TAXI: Evaluating Categorical Knowledge Editing for Language Models. ACL (Findings) 2024: 15343-15352 - [c37]Mike A. Merrill, Mingtian Tan, Vinayak Gupta, Thomas Hartvigsen, Tim Althoff:
Language Models Still Struggle to Zero-shot Reason about Time Series. EMNLP (Findings) 2024: 3512-3533 - [c36]Bryan R. Christ, Jonathan Kropko, Thomas Hartvigsen:
MATHWELL: Generating Educational Math Word Problems Using Teacher Annotations. EMNLP (Findings) 2024: 11914-11938 - [c35]Jack Gallifant, Shan Chen, Pedro Moreira, Nikolaj Munch, Mingye Gao, Jackson Pond, Leo Anthony Celi, Hugo J. W. L. Aerts, Thomas Hartvigsen, Danielle S. Bitterman:
Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks. EMNLP (Findings) 2024: 12448-12465 - [c34]Kumail Alhamoud, Yasir Ghunaim, Motasem Alfarra, Thomas Hartvigsen, Philip Torr, Bernard Ghanem, Adel Bibi, Marzyeh Ghassemi:
FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging. MICCAI (10) 2024: 383-393 - [i27]Sujay Nagaraj, Walter Gerych, Sana Tonekaboni, Anna Goldenberg, Berk Ustun, Thomas Hartvigsen:
Learning from Time Series under Temporal Label Noise. CoRR abs/2402.04398 (2024) - [i26]Kyle O'Brien, Nathan Ng, Isha Puri, Jorge Mendez, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi, Thomas Hartvigsen:
Improving Black-box Robustness with In-Context Rewriting. CoRR abs/2402.08225 (2024) - [i25]Bryan R. Christ, Jonathan Kropko, Thomas Hartvigsen:
MATHWELL: Generating Educational Math Word Problems at Scale. CoRR abs/2402.15861 (2024) - [i24]Shanghua Gao, Teddy Koker, Owen Queen, Thomas Hartvigsen, Theodoros Tsiligkaridis, Marinka Zitnik:
UniTS: Building a Unified Time Series Model. CoRR abs/2403.00131 (2024) - [i23]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
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR abs/2403.01628 (2024) - [i22]Mike A. Merrill, Mingtian Tan, Vinayak Gupta, Tom Hartvigsen, Tim Althoff:
Language Models Still Struggle to Zero-shot Reason about Time Series. CoRR abs/2404.11757 (2024) - [i21]Derek Powell, Walter Gerych, Thomas Hartvigsen:
TAXI: Evaluating Categorical Knowledge Editing for Language Models. CoRR abs/2404.15004 (2024) - [i20]Devansh Jain, Priyanshu Kumar, Samuel Gehman
PolygloToxicityPrompts: Multilingual Evaluation of Neural Toxic Degeneration in Large Language Models. CoRR abs/2405.09373 (2024) - [i19]Shenghuan Sun, Gregory M. Goldgof, Alexander Schubert, Zhiqing Sun, Thomas Hartvigsen, Atul J. Butte, Ahmed M. Alaa:
Dr-LLaVA: Visual Instruction Tuning with Symbolic Clinical Grounding. CoRR abs/2405.19567 (2024) - [i18]Jack Gallifant, Shan Chen, Pedro Moreira, Nikolaj Munch, Mingye Gao, Jackson Pond, Leo Anthony Celi, Hugo J. W. L. Aerts, Thomas Hartvigsen, Danielle S. Bitterman:
Language Models are Surprisingly Fragile to Drug Names in Biomedical Benchmarks. CoRR abs/2406.12066 (2024) - [i17]Mingtian Tan, Mike A. Merrill, Vinayak Gupta, Tim Althoff, Thomas Hartvigsen:
Are Language Models Actually Useful for Time Series Forecasting? CoRR abs/2406.16964 (2024) - [i16]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) - [i15]Kumail Alhamoud, Yasir Ghunaim, Motasem Alfarra, Thomas Hartvigsen, Philip Torr, Bernard Ghanem, Adel Bibi
FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging. CoRR abs/2407.08822 (2024) - [i14]Bernardo Consoli, Xizhi Wu, Song Wang, Xinyu Zhao, Yanshan Wang, Justin F. Rousseau, Tom Hartvigsen, Li Shen, Huanmei Wu, Yifan Peng, Qi Long, Tianlong Chen, Ying Ding:
SDoH-GPT: Using Large Language Models to Extract Social Determinants of Health (SDoH). CoRR abs/2407.17126 (2024) - [i13]Shan Chen, Mingye Gao, Kuleen Sasse, Thomas Hartvigsen, Brian Anthony, Lizhou Fan, Hugo J. W. L. Aerts, Jack Gallifant, Danielle S. Bitterman:
Wait, but Tylenol is Acetaminophen... Investigating and Improving Language Models' Ability to Resist Requests for Misinformation. CoRR abs/2409.20385 (2024) - 2023
- [j1]Sujay Nagaraj, Sarah M. Goodday, Thomas Hartvigsen, Adrien Boch, Kopal Garg, Sindhu C. M. Gowda, Luca Foschini, Marzyeh Ghassemi, Stephen H. Friend, Anna Goldenberg:
Dissecting the heterogeneity of "in the wild" stress from multimodal sensor data. npj Digit. Medicine 6 (2023) - [c33]Jidapa Thadajarassiri, Thomas Hartvigsen, Walter Gerych, Xiangnan Kong, Elke A. Rundensteiner:
Knowledge Amalgamation for Multi-Label Classification via Label Dependency Transfer. AAAI 2023: 9980-9988 - [c32]Hang Yin, Yao Su, Xinyue Liu, Thomas Hartvigsen, Yanhua Li, Xiangnan Kong:
Multi-State Brain Network Discovery. IEEE Big Data 2023: 453-462 - [c31]Walter Gerych, Kevin Hickey, Thomas Hartvigsen, Luke Buquicchio, Abdulaziz Alajaji, Kavin Chandrasekaran, Hamid Mansoor, Emmanuel Agu, Elke A. Rundensteiner:
Stabilizing Adversarial Training for Generative Networks. IEEE Big Data 2023: 5223-5232 - [c30]Elizabeth Bondi-Kelly
Taking Off with AI: Lessons from Aviation for Healthcare. EAAMO 2023: 4:1-4:14 - [c29]Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Kristen Severson, Mercy Nyamewaa Asiedu, Serina Chang, Bonaventure F. P. Dossou, Qian Huang, Fahad Kamran, Haoran Zhang, Sujay Nagaraj, Luis Oala, Shan Xu, Chinasa T. Okolo, Helen Zhou, Jessica Dafflon, Caleb Ellington, Sarah Jabbour, Hyewon Jeong, Harry Reyes Nieva
Machine Learning for Health (ML4H) 2023. ML4H@NeurIPS 2023: 1-12 - [c28]Tom Hartvigsen, Swami Sankaranarayanan, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi:
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors. NeurIPS 2023 - [c27]Owen Queen, Tom Hartvigsen, Teddy Koker, Huan He, Theodoros Tsiligkaridis, Marinka Zitnik:
Encoding Time-Series Explanations through Self-Supervised Model Behavior Consistency. NeurIPS 2023 - [e1]Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Mercy Nyamewaa Asiedu, Serina Chang, Tom Hartvigsen, Harvineet Singh:
Machine Learning for Health, ML4H@NeurIPS 2023, 10 December 2023, New Orleans, Louisiana, USA. Proceedings of Machine Learning Research 225, PMLR 2023 [contents] - [i12]Thomas Hartvigsen, Jidapa Thadajarassiri, Xiangnan Kong, Elke A. Rundensteiner:
Finding Short Signals in Long Irregular Time Series with Continuous-Time Attention Policy Networks. CoRR abs/2302.04052 (2023) - [i11]Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang, Wei Fang, Luc Gaitskell, Thomas Hartvigsen, Xixin Wu, Danny Fox, Helen Meng, James R. Glass:
Interpretable Unified Language Checking. CoRR abs/2304.03728 (2023) - [i10]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) - [i9]Taylor W. Killian, Haoran Zhang, Thomas Hartvigsen, Ava P. Amini:
Continuous Time Evidential Distributions for Irregular Time Series. CoRR abs/2307.13503 (2023) - [i8]Hang Yin, Yao Su, Xinyue Liu, Thomas Hartvigsen, Yanhua Li, Xiangnan Kong:
Multi-State Brain Network Discovery. CoRR abs/2311.02466 (2023) - [i7]Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Mercy Nyamewaa Asiedu, Serina Chang, Thomas Hartvigsen, Harvineet Singh:
Machine Learning for Health symposium 2023 - Findings track. CoRR abs/2312.00655 (2023) - 2022
- [c26]Walter Gerych, Thomas Hartvigsen, Luke Buquicchio, Emmanuel Agu, Elke A. Rundensteiner:
Recovering the Propensity Score from Biased Positive Unlabeled Data. AAAI 2022: 6694-6702 - [c25]Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, Maarten Sap, Dipankar Ray, Ece Kamar:
ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection. ACL (1) 2022: 3309-3326 - [c24]Walter Gerych, Thomas Hartvigsen, Luke Buquicchio, Emmanuel Agu, Elke A. Rundensteiner:
Robust Recurrent Classifier Chains for Multi-Label Learning with Missing Labels. CIKM 2022: 582-591 - [c23]Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri, Xiangnan Kong, Elke A. Rundensteiner:
Stop&Hop: Early Classification of Irregular Time Series. CIKM 2022: 696-705 - [c22]Aparna Balagopalan, Haoran Zhang
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations. FAccT 2022: 1194-1206 - [c21]Ramesh Doddaiah, Prathyush S. Parvatharaju, Elke A. Rundensteiner, Thomas Hartvigsen:
Class-Specific Explainability for Deep Time Series Classifiers. ICDM 2022: 101-110 - [c20]Ruofan Hu, Dongyu Zhang
TWEET-FID: An Annotated Dataset for Multiple Foodborne Illness Detection Tasks. LREC 2022: 6212-6222 - [c19]Walter Gerych, Thomas Hartvigsen, Luke Buquicchio, Abdulaziz Alajaji, Kavin Chandrasekaran, Hamid Mansoor, Elke A. Rundensteiner, Emmanuel Agu:
Positive Unlabeled Learning with a Sequential Selection Bias. SDM 2022: 19-27 - [i6]Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, Maarten Sap, Dipankar Ray, Ece Kamar:
ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection. CoRR abs/2203.09509 (2022) - [i5]Aparna Balagopalan, Haoran Zhang, Kimia Hamidieh, Thomas Hartvigsen, Frank Rudzicz, Marzyeh Ghassemi:
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations. CoRR abs/2205.03295 (2022) - [i4]Ruofan Hu, Dongyu Zhang, Dandan Tao, Thomas Hartvigsen, Hao Feng, Elke A. Rundensteiner:
TWEET-FID: An Annotated Dataset for Multiple Foodborne Illness Detection Tasks. CoRR abs/2205.10726 (2022) - [i3]Thomas Hartvigsen, Walter Gerych, Jidapa Thadajarassiri, Xiangnan Kong, Elke A. Rundensteiner:
Stop&Hop: Early Classification of Irregular Time Series. CoRR abs/2208.09795 (2022) - [i2]Ramesh Doddaiah, Prathyush S. Parvatharaju, Elke A. Rundensteiner, Thomas Hartvigsen:
Class-Specific Explainability for Deep Time Series Classifiers. CoRR abs/2210.05411 (2022) - [i1]Thomas Hartvigsen, Swami Sankaranarayanan, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi:
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors. CoRR abs/2211.11031 (2022) - 2021
- [c18]Jidapa Thadajarassiri, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner:
Semi-Supervised Knowledge Amalgamation for Sequence Classification. AAAI 2021: 9859-9867 - [c17]Dongyu Zhang
Human-like Explanation for Text Classification With Limited Attention Supervision. IEEE BigData 2021: 957-967 - [c16]Luke Buquicchio, Walter Gerych, Abdulaziz Alajaji, Kavin Chandrasekaran, Hamid Mansoor, Thomas Hartvigsen, Elke A. Rundensteiner, Emmanuel Agu:
Variational Open Set Recognition (VOSR). IEEE BigData 2021: 994-1001 - [c15]Prathyush S. Parvatharaju, Ramesh Doddaiah
Learning Saliency Maps to Explain Deep Time Series Classifiers. CIKM 2021: 1406-1415 - [c14]Hang Yin, John Boaz Lee, Xiangnan Kong, Thomas Hartvigsen, Sihong Xie:
Energy-Efficient Models for High-Dimensional Spike Train Classification using Sparse Spiking Neural Networks. KDD 2021: 2017-2025 - [c13]Walter Gerych, Thomas Hartvigsen, Luke Buquicchio, Emmanuel Agu, Elke A. Rundensteiner:
Recurrent Bayesian Classifier Chains for Exact Multi-Label Classification. NeurIPS 2021: 15981-15992 - 2020
- [c12]Cansu Sen, Thomas Hartvigsen, Biao Yin, Xiangnan Kong, Elke A. Rundensteiner:
Human Attention Maps for Text Classification: Do Humans and Neural Networks Focus on the Same Words? ACL 2020: 4596-4608 - [c11]Jidapa Thadajarassiri, Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner:
Learning Similarity-Preserving Meta-Embedding for Text Mining. IEEE BigData 2020: 808-817 - [c10]Erin Teeple, Thomas Hartvigsen, Cansu Sen, Kajal T. Claypool, Elke A. Rundensteiner:
Clinical Performance Evaluation of a Machine Learning System for Predicting Hospital-Acquired Clostridium Difficile Infection. HEALTHINF 2020: 656-663 - [c9]Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner:
Learning to Selectively Update State Neurons in Recurrent Networks. CIKM 2020: 485-494 - [c8]Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner:
Recurrent Halting Chain for Early Multi-label Classification. KDD 2020: 1382-1392
2010 – 2019
- 2019
- [c7]Jidapa Thadajarassiri, Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner:
Comparing General and Locally-Learned Word Embeddings for Clinical Text Mining. BHI 2019: 1-4 - [c6]Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner:
Patient-level Classification on Clinical Note Sequences Guided by Attributed Hierarchical Attention. IEEE BigData 2019: 930-939 - [c5]Cansu Sen, Thomas Hartvigsen, Xiangnan Kong, Elke A. Rundensteiner:
Learning Temporal Relevance in Longitudinal Medical Notes. IEEE BigData 2019: 2474-2483 - [c4]Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner:
Adaptive-Halting Policy Network for Early Classification. KDD 2019: 101-110 - 2018
- [c3]Thomas Hartvigsen, Cansu Sen, Sarah Brownell, Erin Teeple, Xiangnan Kong, Elke A. Rundensteiner:
Early Prediction of MRSA Infections using Electronic Health Records. HEALTHINF 2018: 156-167 - [c2]Thomas Hartvigsen, Cansu Sen, Elke A. Rundensteiner:
Detecting MRSA Infections by Fusing Structured and Unstructured Electronic Health Record Data. BIOSTEC (Selected Papers) 2018: 399-419 - 2017
- [c1]Cansu Sen, Thomas Hartvigsen, Elke A. Rundensteiner, Kajal T. Claypool:
CREST - Risk Prediction for Clostridium Difficile Infection Using Multimodal Data Mining. ECML/PKDD (3) 2017: 52-63
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-19 20:45 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: