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Found 6 papers, 3 papers with code
FREE: The Foundational Semantic Recognition for Modeling Environmental Ecosystems
This raises a fundamental question in advancing the modeling of environmental ecosystems: how to build a general framework for modeling the complex relationships amongst various environmental data over space and time?
Knowledge Guided Representation Learning and Causal Structure Learning in Soil Science
Process-based models and analyzing observed data provide two avenues for improving our understanding of soil processes.
Task-Adaptive Meta-Learning Framework for Advancing Spatial Generalizability
One major advantage of our proposed method is that it improves the model adaptation to a large number of heterogeneous tasks.
Mini-Batch Learning Strategies for modeling long term temporal dependencies: A study in environmental applications
To address this issue, we further propose a new strategy which augments a training segment with an initial value of the target variable from the timestep right before the starting of the training segment.
Binary Representation via Jointly Personalized Sparse Hashing
Different personalized subspaces are constructed to reflect category-specific attributes for different clusters, adaptively mapping instances within the same cluster to the same Hamming space.
Updating the silent speech challenge benchmark with deep learning
The 2010 Silent Speech Challenge benchmark is updated with new results obtained in a Deep Learning strategy, using the same input features and decoding strategy as in the original article.
