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2020 – today
- 2025
[c3]Andrin Rehmann
, Dion Häfner, Alessandro Angioi, Yongquan Qu, Andrei Paleyes:
Pipeline-level differentiable programming for the real world. SciPy 2025: 278-285- [i6]Matthieu Blanke, Yongquan Qu, Sara Shamekh, Pierre Gentine:
Strictly Constrained Generative Modeling via Split Augmented Langevin Sampling. CoRR abs/2505.18017 (2025) - [i5]Yongquan Qu, Matthieu Blanke, Sara Shamekh, Pierre Gentine:
PnP-DA: Towards Principled Plug-and-Play Integration of Variational Data Assimilation and Generative Models. CoRR abs/2508.00325 (2025) - [i4]Hang Fan, Yi Xiao, Yongquan Qu, Fenghua Ling, Ben Fei, Lei Bai, Pierre Gentine:
Incorporating Multivariate Consistency in ML-Based Weather Forecasting with Latent-space Constraints. CoRR abs/2510.04006 (2025) - 2024
- [c2]Yongquan Qu, Juan Nathaniel, Shuolin Li, Pierre Gentine:
Deep Generative Data Assimilation in Multimodal Setting. CVPR Workshops 2024: 449-459 - [c1]Juan Nathaniel, Yongquan Qu, Tung Nguyen, Sungduk Yu, Julius Busecke, Aditya Grover, Pierre Gentine:
ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction. NeurIPS 2024 - [i3]Juan Nathaniel, Yongquan Qu, Tung Nguyen, Sungduk Yu, Julius Busecke, Aditya Grover, Pierre Gentine:
ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction. CoRR abs/2402.00712 (2024) - [i2]Yongquan Qu, Mohamed Aziz Bhouri, Pierre Gentine:
Joint Parameter and Parameterization Inference with Uncertainty Quantification through Differentiable Programming. CoRR abs/2403.02215 (2024) - [i1]Yongquan Qu, Juan Nathaniel, Shuolin Li, Pierre Gentine:
Deep Generative Data Assimilation in Multimodal Setting. CoRR abs/2404.06665 (2024)
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