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ArticlesPeer ReviewedFull Text
Global Wildfire Susceptibility Mapping Based on Machine Learning Models
Author / Creator:Shmuel, Assaf ; Heifetz, Eyal
Publisher:Basel: MDPI AG
Journal title:Forests, 2022-07, Vol.13 (7), p.1050
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ArticlesPeer ReviewedFull Text
Re-examining the assumption of dominant regional wind and fire spread directions
Author / Creator:Shmuel, Assaf ; Heifetz, Eyal
Publisher:Roslyn: CSIRO
Journal title:International journal of wildland fire, 2022-01, Vol.31 (5), p.480-491
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ArticlesPeer ReviewedFull Text
Global lightning-ignited wildfires prediction and climate change projections based on explainable machine learning models
Author / Creator:Shmuel, Assaf ; Lazebnik, Teddy ; Glickman, Oren ; Heifetz, Eyal ; Price, Colin
Publisher:England: Nature Publishing Group
Journal title:Scientific reports, 2025-03, Vol.15 (1), p.7898-13, Article 7898
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ArticlesPeer ReviewedFull Text
A Machine-Learning Approach to Predicting Daily Wildfire Expansion Rate
Author / Creator:Shmuel, Assaf ; Heifetz, Eyal
Publisher:Basel: MDPI AG
Journal title:Fire (Basel, Switzerland), 2023-08, Vol.6 (8), p.319
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ArticlesPeer ReviewedFull Text
Developing novel machine-learning-based fire weather indices
Author / Creator:Shmuel, Assaf ; Heifetz, Eyal
Publisher:Bristol: IOP Publishing
Journal title:Machine learning: science and technology, 2023-03, Vol.4 (1), p.15029
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ArticlesPeer ReviewedFull Text
Empirical Evidence of Reduced Wildfire Ignition Risk in the Presence of Strong Winds
Author / Creator:Shmuel, Assaf ; Heifetz, Eyal
Publisher:Basel: MDPI AG
Journal title:Fire (Basel, Switzerland), 2023-09, Vol.6 (9), p.338
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ArticlesPeer ReviewedFull Text
A Dijkstra-Based Approach to Fuelbreak Planning
Author / Creator:Shmuel, Assaf ; Heifetz, Eyal
Publisher:Basel: MDPI AG
Journal title:Fire (Basel, Switzerland), 2023-08, Vol.6 (8), p.295
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ArticlesPeer ReviewedFull Text
Symbolic regression as a feature engineering method for machine and deep learning regression tasks
Author / Creator:Shmuel, Assaf ; Glickman, Oren ; Lazebnik, Teddy
Publisher:Bristol: IOP Publishing
Journal title:Machine learning: science and technology, 2024-06, Vol.5 (2), p.25065
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ArticlesPeer ReviewedFull Text
Machine and deep learning performance in out-of-distribution regressions
Author / Creator:Shmuel, Assaf ; Glickman, Oren ; Lazebnik, Teddy
Publisher:Bristol: IOP Publishing
Journal title:Machine learning: science and technology, 2024-12, Vol.5 (4), p.45078
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ArticlesFull Text
Symbolic Regression as Feature Engineering Method for Machine and Deep Learning Regression Tasks
Author / Creator:Assaf Shmuel ; Glickman, Oren ; Lazebnik, Teddy
Publisher:Ithaca: Cornell University Library, arXiv.org
Journal title:arXiv.org, 2023-11
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ArticlesPeer ReviewedFull Text
Global lightning-ignited wildfires prediction and climate change projections based on explainable machine learning models: Global Lightning-Ignited Wildfires Prediction and Climate Change Pr
Author / Creator:Shmuel, Assaf ; Lazebnik, Teddy ; Glickman, Oren ; Heifetz, Eyal ; Price, Colin
Publisher:London: Nature Publishing Group UK
Journal title:Scientific reports, 2025-03, Vol.15 (1)
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ArticlesFull Text
Rubisco is slow across the tree of life
Author / Creator:De Pins, Benoit ; Malbranke, Cyril ; Jablonska, Jagoda ; Assaf Shmuel ; Itai, Sharon ; Anne-Florence Bitbol ; Mueller-Cajar, Oliver ; Noor, Elad ; Milo, Ron
Publisher:Cold Spring Harbor: Cold Spring Harbor Laboratory Press
Journal title:bioRxiv, 2025-01
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ArticlesFull Text
A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
Author / Creator:Assaf Shmuel ; Glickman, Oren ; Lazebnik, Teddy
Publisher:Ithaca: Cornell University Library, arXiv.org
Journal title:arXiv.org, 2024-08
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ArticlesFull Text
Global Lightning-Ignited Wildfires Prediction and Climate Change Projections based on Explainable Machine Learning Models
Author / Creator:Assaf Shmuel ; Lazebnik, Teddy ; Glickman, Oren ; Heifetz, Eyal ; Price, Colin
Publisher:Ithaca: Cornell University Library, arXiv.org
Journal title:arXiv.org, 2024-09
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Global Wildfire Susceptibility Mapping Based on Machine Learning Models

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Re-examining the assumption of dominant regional wind and fire spread directions

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Global lightning-ignited wildfires prediction and climate change projections based on explainable machine learning models

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A Machine-Learning Approach to Predicting Daily Wildfire Expansion Rate

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Developing novel machine-learning-based fire weather indices

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Empirical Evidence of Reduced Wildfire Ignition Risk in the Presence of Strong Winds

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A Dijkstra-Based Approach to Fuelbreak Planning

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Symbolic regression as a feature engineering method for machine and deep learning regression tasks

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Machine and deep learning performance in out-of-distribution regressions

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Symbolic Regression as Feature Engineering Method for Machine and Deep Learning Regression Tasks

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Global lightning-ignited wildfires prediction and climate change projections based on explainable machine learning models: Global Lightning-Ignited Wildfires Prediction and Climate Change Pr

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Rubisco is slow across the tree of life

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A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets

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Global Lightning-Ignited Wildfires Prediction and Climate Change Projections based on Explainable Machine Learning Models

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