In recent years, we have witnessed a significant shift toward ever-more complex and ever-
larger-scale systems in the majority of the grand societal challenges tackled in applied …

Transformer architectures have widespread applications, particularly in Natural Language
Processing and Computer Vision. Recently, Transformers have been employed in various …

Understanding the interplay of order and disorder in chaos is a central challenge in modern
quantitative science. Approximate linear representations of nonlinear dynamics have long …

Single-cell RNA sequencing (RNA-Seq) provides rich information about cell types and
states. However, it is difficult to capture rare dynamic processes, such as adult …

Because of global warming, Earth's ecosystems have been experiencing more frequent and
severe heatwaves. Heatwaves are expected to tip terrestrial carbon sequestration by …

Identifying causal networks is important for effective policy and management
recommendations on climate, epidemiology, financial regulation, and much else. We …

Evolution is the hallmark of life. Descriptions of the evolution of microorganisms have
provided a wealth of information, but knowledge regarding “what happened” has precluded …

An important problem across many scientific fields is the identification of causal effects from
observational data alone. Recent methods (convergent cross map**, CCM) have made …

In temperate countries, influenza outbreaks are well correlated to seasonal changes in
temperature and absolute humidity. However, tropical countries have much weaker annual …

Electroencephalogram (EEG) signals acquired from brain can provide an effective
representation of the human's physiological and pathological states. Up to now, much work …