Mike A. Merrill

According to our database, Mike A. Merrill authored at least 10 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Are Language Models Actually Useful for Time Series Forecasting?

Mingtian Tan, Mike A. Merrill, Vinayak Gupta, Tim Althoff, Thomas Hartvigsen

CoRR, 2024

Transforming Wearable Data into Health Insights using Large Language Model Agents.

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

CoRR, 2024

Language Models Still Struggle to Zero-shot Reason about Time Series.

Mike A. Merrill, Mingtian Tan, Vinayak Gupta, Thomas Hartvigsen, Tim Althoff

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

BLADE: Benchmarking Language Model Agents for Data-Driven Science.

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

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

Homekit2020: A Benchmark for Time Series Classification on a Large Mobile Sensing Dataset with Laboratory Tested Ground Truth of Influenza Infections.

Mike A. Merrill, Esteban Safranchik, Arinbjörn Kolbeinsson, Piyusha Gade, Ernesto Ramirez, Ludwig Schmidt, Luca Foshchini, Tim Althoff

Proceedings of the Conference on Health, Inference, and Learning, 2023

Self-Supervised Pretraining and Transfer Learning Enable Flu and COVID-19 Predictions in Small Mobile Sensing Datasets.

Mike A. Merrill, Tim Althoff

Proceedings of the Conference on Health, Inference, and Learning, 2023

2022

CORAL: COde RepresentAtion learning with weakly-supervised transformers for analyzing data analysis.

Ge Zhang, Mike A. Merrill, Yang Liu, Jeffrey Heer, Tim Althoff

EPJ Data Sci., 2022

GLOBEM Dataset: Multi-Year Datasets for Longitudinal Human Behavior Modeling Generalization.

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

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Transformer-Based Behavioral Representation Learning Enables Transfer Learning for Mobile Sensing in Small Datasets.

Mike A. Merrill, Tim Althoff

CoRR, 2021

MULTIVERSE: Mining Collective Data Science Knowledge from Code on the Web to Suggest Alternative Analysis Approaches.

Mike A. Merrill, Ge Zhang, Tim Althoff

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021