Tom Hartvigsen
Tom Hartvigsen
Otros nombresThomas Hartvigsen
Assistant Professor, University of Virginia
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ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection
T Hartvigsen, S Gabriel, H Palangi, M Sap, D Ray, E Kamar
ACL 2022, 2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations
A Balagopalan, H Zhang, K Hamidieh, T Hartvigsen, F Rudzicz, ...
FAccT 2022, 2022
Human attention maps for text classification: Do humans and neural networks focus on the same words?
C Sen, T Hartvigsen, B Yin, X Kong, ER Rundensteiner
ACL 2020, 2020
Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors
T Hartvigsen, S Sankaranarayanan, H Palangi, Y Kim, M Ghassemi
NeurIPS 2023, 2023
Adaptive-Halting Policy Network for Early Classification
T Hartvigsen, C Sen, X Kong, E Rundensteiner
KDD 2019, 2019
Learning Saliency Maps to Explain Deep Time Series Classifiers
P Parvatharaju, R Doddaiah, T Hartvigsen, E Rundensteiner
CIKM 2021, 2021
Early Prediction of MRSA Infections using Electronic Health Records
T Hartvigsen, C Sen, S Brownell, E Teeple, X Kong, EA Rundensteiner
International Conference on Health Informatics, 156-167, 2018
Recurrent Bayesian Classifier Chains for Exact Multi-label Classification
W Gerych, T Hartvigsen, L Buquicchio, E Agu, E Rundensteiner
NeurIPS 2021, 2021
Recurrent Halting Chain for Early Multi-label Classification
T Hartvigsen, C Sen, X Kong, E Rundensteiner
KDD 2020, 2020
Interpretable unified language checking
T Zhang, H Luo, YS Chuang, W Fang, L Gaitskell, T Hartvigsen, X Wu, ...
arXiv preprint arXiv:2304.03728, 2023
Recovering the Propensity Score from Biased Positive Unlabeled Data
W Gerych, T Hartvigsen, L Buquicchio, E Agu, E Rundensteiner
AAAI 2022, 2022
Crest-risk prediction for clostridium difficile infection using multimodal data mining
C Sen, T Hartvigsen, E Rundensteiner, K Claypool
ECML 2017, 2017
Stop&Hop: Early Classification of Irregular Time Series
T Hartvigsen, W Gerych, J Thadajarassiri, X Kong, E Rundensteiner
CIKM 2022, 2022
Semi-Supervised Knowledge Amalgamation for Sequence Classification
J Thadajarassiri, T Hartvigsen, X Kong, E Rundensteiner
AAAI 2021, 2021
Energy-Efficient Models for High-Dimensional Spike Train Classification using Sparse Spiking Neural Networks
H Yin, J Lee, X Kong, T Hartvigsen, S Xie
KDD 2021, 2021
Units: Building a unified time series model
S Gao, T Koker, O Queen, T Hartvigsen, T Tsiligkaridis, M Zitnik
arXiv preprint arXiv:2403.00131, 2024
Encoding time-series explanations through self-supervised model behavior consistency
O Queen, T Hartvigsen, T Koker, H He, T Tsiligkaridis, M Zitnik
Advances in Neural Information Processing Systems 36, 2023
TWEET-FID: An Annotated Dataset for Multiple Foodborne Illness Detection Tasks
R Hu, D Zhang, D Tao, T Hartvigsen, H Feng, E Rundensteiner
LREC 2022, 2022
Patient-level classification on clinical note sequences guided by attributed hierarchical attention
C Sen, T Hartvigsen, X Kong, E Rundensteiner
IEEE International Conference on Big Data (Big Data), 930-939, 2019
Demographic bias in misdiagnosis by computational pathology models
A Vaidya, RJ Chen, DFK Williamson, AH Song, G Jaume, Y Yang, ...
Nature Medicine 30 (4), 1174-1190, 2024
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