6 papers
Chemistry-aware battery degradation prediction under simulated real-world cyclic protocols
Yuqi Li, Han Zhang, Xiaofan Gui +10
Battery degradation is governed by complex and randomized cyclic conditions, yet existing modeling and prediction frameworks usually rely on rigid, unchanging protocols that fail t…
Near-real-time monitoring of global ocean carbon sink
Piyu Ke, Xiaofan Gui, Wei Cao +11
Mitigation of climate change will highly rely on a carbon emission trajectory that achieves carbon neutrality by the 2050s. The ocean plays a critical role in modulating climate ch…
Accurate battery lifetime prediction across diverse aging conditions with deep learning
Han Zhang, Yuqi Li, Shun Zheng +4
Accurately predicting the lifetime of battery cells in early cycles holds tremendous value for battery research and development as well as numerous downstream applications. This ta…
BatteryML:An Open-source platform for Machine Learning on Battery Degradation
Han Zhang, Xiaofan Gui, Shun Zheng +3
Battery degradation remains a pivotal concern in the energy storage domain, with machine learning emerging as a potent tool to drive forward insights and solutions. However, this i…
NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time-Series Pretraining
Chenguo Lin, Xumeng Wen, Wei Cao +4
Recent research on time-series self-supervised models shows great promise in learning semantic representations. However, it has been limited to small-scale datasets, e.g., thousand…
From Supervised to Generative: A Novel Paradigm for Tabular Deep Learning with Large Language Models
Xumeng Wen, Han Zhang, Shun Zheng +2
Tabular data is foundational to predictive modeling in various crucial industries, including healthcare, finance, retail, sustainability, etc. Despite the progress made in speciali…