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2020 – today
- 2024
[i8]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)- [i7]Mike A. Merrill, Akshay Paruchuri, Naghmeh Rezaei, Geza Kovacs, Javier Perez Matos, Yun Liu, Erik Schenck, Nova Hammerquist, Jake Sunshine, Shyam Tailor, Kumar Ayush, Hao-Wei Su, Qian He, Cory Y. McLean, Mark Malhotra, Shwetak N. Patel, Jiening Zhan, Tim Althoff, Daniel McDuff, Xin Liu:
Transforming Wearable Data into Health Insights using Large Language Model Agents. CoRR abs/2406.06464 (2024) - [i6]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) - [i5]Ken Gu, Ruoxi Shang, Ruien Jiang, Keying Kuang, Richard-John Lin, Donghe Lyu, Yue Mao, Youran Pan, Teng Wu, Jiaqian Yu, Yikun Zhang, Tianmai M. Zhang, Lanyi Zhu, Mike A. Merrill, Jeffrey Heer, Tim Althoff:
BLADE: Benchmarking Language Model Agents for Data-Driven Science. CoRR abs/2408.09667 (2024) - 2023
- [c4]Mike A. Merrill, Tim Althoff:
Self-Supervised Pretraining and Transfer Learning Enable Flu and COVID-19 Predictions in Small Mobile Sensing Datasets. CHIL 2023: 191-206 - [c3]Mike A. Merrill, Esteban Safranchik, Arinbjörn Kolbeinsson, Piyusha Gade, Ernesto Ramirez, Ludwig Schmidt, Luca Foshchini, Tim Althoff:
Homekit2020: A Benchmark for Time Series Classification on a Large Mobile Sensing Dataset with Laboratory Tested Ground Truth of Influenza Infections. CHIL 2023: 207-228 - 2022
- [j1]Ge Zhang
, Mike A. Merrill, Yang Liu, Jeffrey Heer, Tim Althoff:
CORAL: COde RepresentAtion learning with weakly-supervised transformers for analyzing data analysis. EPJ Data Sci. 11(1): 14 (2022) - [c2]Xuhai Xu, Han Zhang, Yasaman S. Sefidgar, Yiyi Ren, Xin Liu, Woosuk Seo, Jennifer Brown, Kevin S. Kuehn, Mike A. Merrill, Paula S. Nurius, Shwetak N. Patel, Tim Althoff, Margaret E. Morris, Eve A. Riskin, Jennifer Mankoff, Anind K. Dey:
GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling Generalization. NeurIPS 2022 - [i4]Mike A. Merrill, Tim Althoff:
Self-supervised Pretraining and Transfer Learning Enable Flu and COVID-19 Predictions in Small Mobile Sensing Datasets. CoRR abs/2205.13607 (2022) - [i3]Xuhai Xu, Han Zhang, Yasaman S. Sefidgar, Yiyi Ren, Xin Liu, Woosuk Seo, Jennifer Brown, Kevin S. Kuehn, Mike A. Merrill, Paula S. Nurius, Shwetak N. Patel, Tim Althoff, Margaret E. Morris, Eve A. Riskin, Jennifer Mankoff, Anind K. Dey:
GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling Generalization. CoRR abs/2211.02733 (2022) - 2021
- [c1]Mike A. Merrill, Ge Zhang, Tim Althoff:
MULTIVERSE: Mining Collective Data Science Knowledge from Code on the Web to Suggest Alternative Analysis Approaches. KDD 2021: 1212-1222 - [i2]Mike A. Merrill, Tim Althoff:
Transformer-Based Behavioral Representation Learning Enables Transfer Learning for Mobile Sensing in Small Datasets. CoRR abs/2107.06097 (2021) - 2020
- [i1]Ge Zhang, Mike A. Merrill, Yang Liu, Jeffrey Heer, Tim Althoff:
CORAL: COde RepresentAtion Learning with Weakly-Supervised Transformers for Analyzing Data Analysis. CoRR abs/2008.12828 (2020)
Coauthor Index
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