Context-Aware Graph Convolutional Network for Dynamic Origin-Destination Prediction. - Juan Nathaniel; Baihua Zheng (IEEE BigData, 2021)

NetZeroCO2, an AI framework for accelerated nature-based carbon sequestration. - Ademir Ferreira da Silva; Juan Nathaniel; Ken C. L. Wong; Campbell D. Watson; Hongzhi Wang 002; Jitendra Singh; Alexandre Alkmim Chamon; Levente J. Klein (IEEE Big Data, 2022)

Aboveground carbon biomass estimate with Physics-informed deep network. - Juan Nathaniel; Levente J. Klein; Campbell D. Watson; Gabrielle Nyirjesy; Conrad M. Albrecht (CoRR, 2022)

Above Ground Carbon Biomass Estimate with Physics-Informed Deep Network. - Juan Nathaniel; Gabrielle Nyirjesy; Campbell D. Watson; Conrad M. Albrecht; Levente J. Klein (IGARSS, 2023)

Deep Generative Data Assimilation in Multimodal Setting. - Yongquan Qu; Juan Nathaniel; Shuolin Li; Pierre Gentine (CVPR Workshops, 2024)

ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction. - Juan Nathaniel; Yongquan Qu; Tung Nguyen; Sungduk Yu; Julius Busecke; Aditya Grover; Pierre Gentine (NeurIPS, 2024)

Generative emulation of chaotic dynamics with coherent prior. - Juan Nathaniel; Pierre Gentine (CoRR, 2025)

Deep Koopman operator framework for causal discovery in nonlinear dynamical systems. - Juan Nathaniel; Carla Roesch; Jatan Buch; Derek DeSantis; Adam Rupe; Kara Lamb; Pierre Gentine (CoRR, 2025)

CausalDynamics: A large-scale benchmark for structural discovery of dynamical causal models. - Benjamin Herdeanu; Juan Nathaniel; Carla Roesch; Jatan Buch; Gregor N. Ramien; Johannes Haux; Pierre Gentine (CoRR, 2025)