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Found 9 papers, 4 papers with code
Knowledge Guided Encoder-Decoder Framework: Integrating Multiple Physical Models for Agricultural Ecosystem Modeling
Agricultural monitoring is critical for ensuring food security, maintaining sustainable farming practices, informing policies on mitigating food shortage, and managing greenhouse gas emissions.
RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning
Training large language models (LLMs) as interactive agents presents unique challenges including long-horizon decision making and interacting with stochastic environment feedback.
Hierarchical Conditional Multi-Task Learning for Streamflow Modeling
To address this, we propose Hierarchical Conditional Multi-Task Learning (HCMTL), a hierarchical approach that jointly models soil water and snowpack processes based on their causal connections to streamflow.
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.
