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Found 7 papers, 0 papers with code
Task Aware Modulation using Representation Learning: An Approach for Few Shot Learning in Heterogeneous Systems
We present a Task-aware modulation using Representation Learning (TAM-RL) framework that enhances personalized predictions in few-shot settings for heterogeneous systems when individual task characteristics are not known.
Uncertainty Quantification in Inverse Models in Hydrology
Our inverse model offers 3\% improvement in R$^2$ for the inverse model (basin characteristic estimation) and 6\% for the forward model (streamflow prediction).
Message Propagation Through Time: An Algorithm for Sequence Dependency Retention in Time Series Modeling
Time series modeling, a crucial area in science, often encounters challenges when training Machine Learning (ML) models like Recurrent Neural Networks (RNNs) using the conventional mini-batch training strategy that assumes independent and identically distributed (IID) samples and initializes RNNs with zero hidden states.
Koopman Invertible Autoencoder: Leveraging Forward and Backward Dynamics for Temporal Modeling
Accurate long-term predictions are the foundations for many machine learning applications and decision-making processes.
Entity Aware Modelling: A Survey
However, these entity characteristics are not readily available in many real-world scenarios, and different ML methods have been proposed to infer these characteristics from the data.
Probabilistic Inverse Modeling: An Application in Hydrology
We propose uncertainty based learning method that offers 6\% improvement in $R^2$ for streamflow prediction (forward modeling) from inverse model inferred basin characteristic estimates, 17\% reduction in uncertainty (40\% in presence of noise) and 4\% higher coverage rate for basin characteristics.
Robust Inverse Framework using Knowledge-guided Self-Supervised Learning: An application to Hydrology
Furthermore, we show that KGSSL is relatively more robust to distortion than baseline methods, and outperforms the baseline model by 35\% when plugging in KGSSL inferred characteristics.
