Summary of Setpinns: Set-based Physics-informed Neural Networks, by Mayank Nagda et al.
SetPINNs: Set-based Physics-informed Neural Networksby Mayank Nagda, Phil Ostheimer, Thomas Specht, Frank Rhein, Fabian Jirasek,…
SetPINNs: Set-based Physics-informed Neural Networksby Mayank Nagda, Phil Ostheimer, Thomas Specht, Frank Rhein, Fabian Jirasek,…
A Survey on Graph Neural Networks for Remaining Useful Life Prediction: Methodologies, Evaluation and Future…
TensorSocket: Shared Data Loading for Deep Learning Trainingby Ties Robroek, Neil Kim Nielsen, Pınar TözünFirst…
HardCore Generation: Generating Hard UNSAT Problems for Data Augmentationby Joseph Cotnareanu, Zhanguang Zhang, Hui-Ling Zhen,…
HR-Extreme: A High-Resolution Dataset for Extreme Weather Forecastingby Nian Ran, Peng Xiao, Yue Wang, Wesley…
TemporalPaD: a reinforcement-learning framework for temporal feature representation and dimension reductionby Xuechen Mu, Zhenyu Huang,…
MALPOLON: A Framework for Deep Species Distribution Modelingby Theo Larcher, Lukas Picek, Benjamin Deneu, Titouan…
SLIDE: A machine-learning based method for forced dynamic response estimation of multibody systemsby Peter Manzl,…
Efficient Bias Mitigation Without Privileged Informationby Mateo Espinosa Zarlenga, Swami Sankaranarayanan, Jerone T. A. Andrews,…
Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate Databy Alif Bin…