Zobrazeno 1 - 10
of 3 064
pro vyhledávání: '"Chace A"'
Autor:
Derek Rollend, Kevin Foster, Tomek M. Kott, Rohita Mocharla, Rai Muñoz, Neil Fendley, Chace Ashcraft, Frank Willard, Elizabeth P. Reilly, Marisa Hughes
Publikováno v:
Environmental Data Science, Vol 2 (2023)
Measuring and attributing greenhouse gas (GHG) emissions remains a challenging problem as the world strives toward meeting emissions reductions targets. As a significant portion of total global emissions, the road transportation sector represents an
Externí odkaz:
https://doaj.org/article/9b08abed83ba46919fc7198b1a3b690d
Autor:
Corban Rivera, Katie M. Popek, Chace Ashcraft, Edward W. Staley, Kapil D. Katyal, Bart L. Paulhamus
Publikováno v:
Frontiers in Neurorobotics, Vol 16 (2022)
Generalizing prior experiences to complete new tasks is a challenging and unsolved problem in robotics. In this work, we explore a novel framework for control of complex systems called Primitive Imitation for Control (PICO). The approach combines ide
Externí odkaz:
https://doaj.org/article/a880c55be16a4d2c987e1f4abf81e1e2
Autor:
Cosentino, Justin, Belyaeva, Anastasiya, Liu, Xin, Furlotte, Nicholas A., Yang, Zhun, Lee, Chace, Schenck, Erik, Patel, Yojan, Cui, Jian, Schneider, Logan Douglas, Bryant, Robby, Gomes, Ryan G., Jiang, Allen, Lee, Roy, Liu, Yun, Perez, Javier, Rogers, Jameson K., Speed, Cathy, Tailor, Shyam, Walker, Megan, Yu, Jeffrey, Althoff, Tim, Heneghan, Conor, Hernandez, John, Malhotra, Mark, Stern, Leor, Matias, Yossi, Corrado, Greg S., Patel, Shwetak, Shetty, Shravya, Zhan, Jiening, Prabhakara, Shruthi, McDuff, Daniel, McLean, Cory Y.
In health, most large language model (LLM) research has focused on clinical tasks. However, mobile and wearable devices, which are rarely integrated into such tasks, provide rich, longitudinal data for personal health monitoring. Here we present Pers
Externí odkaz:
http://arxiv.org/abs/2406.06474
Autor:
Chen, Reed River, Ribaudo, Christopher, Sleeman, Jennifer, Ashcraft, Chace, Kofroth, Collin, Hughes, Marisa, Stajner, Ivanka, Viner, Kevin, Wang, Kai
Human health is negatively impacted by poor air quality including increased risk for respiratory and cardiovascular disease. Due to a recent increase in extreme air quality events, both globally and locally in the United States, finer resolution air
Externí odkaz:
http://arxiv.org/abs/2402.14806
Autor:
Paleja, Rohan, Chen, Letian, Niu, Yaru, Silva, Andrew, Li, Zhaoxin, Zhang, Songan, Ritchie, Chace, Choi, Sugju, Chang, Kimberlee Chestnut, Tseng, Hongtei Eric, Wang, Yan, Nageshrao, Subramanya, Gombolay, Matthew
Interpretability in machine learning is critical for the safe deployment of learned policies across legally-regulated and safety-critical domains. While gradient-based approaches in reinforcement learning have achieved tremendous success in learning
Externí odkaz:
http://arxiv.org/abs/2311.10041
Autor:
Shang, Helen H., Nasr, Mohammad Sadegh, Veerla, Jai Prakash, Malidarreh, Parisa Boodaghi, Saurav, MD Jillur Rahman, Hajighasemi, Amir, Huber, Manfred, Moleta, Chace, Makker, Jitin, Luber, Jacob M.
The search and retrieval of digital histopathology slides is an important task that has yet to be solved. In this case study, we investigate the clinical readiness of three state-of-the-art histopathology slide search engines, Yottixel, SISH, and Ret
Externí odkaz:
http://arxiv.org/abs/2306.17019
In recent years, there has been an increase in using deep learning for climate and weather modeling. Though results have been impressive, explainability and interpretability of deep learning models are still a challenge. A third wave of Artificial In
Externí odkaz:
http://arxiv.org/abs/2306.11161
Autor:
Sleeman, Jennifer, Chung, David, Gnanadesikan, Anand, Brett, Jay, Kevrekidis, Yannis, Hughes, Marisa, Haine, Thomas, Pradal, Marie-Aude, Gelderloos, Renske, Ashcraft, Chace, Tang, Caroline, Saksena, Anshu, White, Larry
We propose a new Tipping Point Generative Adversarial Network (TIP-GAN) for better characterizing potential climate tipping points in Earth system models. We describe an adversarial game to explore the parameter space of these models, detect upcoming
Externí odkaz:
http://arxiv.org/abs/2302.10274
Autor:
Sleeman, Jennifer, Chung, David, Ashcraft, Chace, Brett, Jay, Gnanadesikan, Anand, Kevrekidis, Yannis, Hughes, Marisa, Haine, Thomas, Pradal, Marie-Aude, Gelderloos, Renske, Tang, Caroline, Saksena, Anshu, White, Larry
We propose a hybrid Artificial Intelligence (AI) climate modeling approach that enables climate modelers in scientific discovery using a climate-targeted simulation methodology based on a novel combination of deep neural networks and mathematical met
Externí odkaz:
http://arxiv.org/abs/2302.06852
The deployment of machine learning models in safety-critical applications comes with the expectation that such models will perform well over a range of contexts (e.g., a vision model for classifying street signs should work in rural, city, and highwa
Externí odkaz:
http://arxiv.org/abs/2211.15436