TIML: Task-Informed Meta-Learning for Agriculture

4 February 2022

Papers citing "TIML: Task-Informed Meta-Learning for Agriculture"

9 / 9 papers shown

Title
Application-Driven Innovation in Machine Learning David Rolnick Alán Aspuru-Guzik Sara Beery B. Dilkina P. Donti ... Hannah Kerner C. Monteleoni Esther Rolf Milind Tambe Adam White 36 8 0 26 Mar 2024
In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing Data Francisco Mena Diego Arenas A. Dengel 46 2 0 25 Mar 2024
SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery Konstantin Klemmer Esther Rolf Caleb Robinson Lester Mackey M. Rußwurm SSL 15 64 0 28 Nov 2023
Bidirectional recurrent imputation and abundance estimation of LULC classes with MODIS multispectral time series and geo-topographic and climatic data José Rodríguez-Ortega Rohaifa Khaldi D. Alcaraz‐Segura S. Tabik 14 1 0 11 Oct 2023
Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks M. Rußwurm Konstantin Klemmer Esther Rolf Robin Zbinden D. Tuia 35 34 0 10 Oct 2023
Machine Learning and Deep Learning -- A review for Ecologists Maximilian Pichler F. Hartig 42 127 0 11 Apr 2022
SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning Christopher Yeh Chenlin Meng Sherrie Wang Anne Driscoll Erik Rozi Patrick Liu Jihyeon Janel Lee Marshall Burke David B. Lobell Stefano Ermon 62 56 0 08 Nov 2021
Crop mapping from image time series: deep learning with multi-scale label hierarchies Mehmet Özgür Türkoglu Stefano Dáronco Gregor Perich F. Liebisch Constantin Streit Konrad Schindler Jan Dirk Wegner 87 129 0 17 Feb 2021
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 326 11,681 0 09 Mar 2017