Assaf Shmuel

According to our database, Assaf Shmuel authored at least 9 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Interpretable knowledge distillation via symbolic regression for feedforward neural networks.

Assaf Shmuel, Nir Koren, Oren Glickman, Teddy Lazebnik

Neural Comput. Appl., April, 2026

Follow the Forest Trail: Distillation by Gradient Boosting Models to Enhance Symbolic Regression Performance.

Assaf Shmuel, Teddy Lazebnik, Oren Glickman

IEEE Access, 2026

2025

Data Augmentation for Deep Learning Regression Tasks by Machine Learning Models.

Assaf Shmuel, Oren Glickman, Teddy Lazebnik

CoRR, January, 2025

A comprehensive benchmark of machine and deep learning models on structured data for regression and classification.

Assaf Shmuel, Oren Glickman, Teddy Lazebnik

Neurocomputing, 2025

2024

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

Assaf Shmuel, Oren Glickman, Teddy Lazebnik

Mach. Learn. Sci. Technol., 2024

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

Assaf Shmuel, Oren Glickman, Teddy Lazebnik

Mach. Learn. Sci. Technol., 2024

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

Assaf Shmuel, Teddy Lazebnik, Oren Glickman, Eyal Heifetz, Colin Price

CoRR, 2024

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

Assaf Shmuel, Oren Glickman, Teddy Lazebnik

CoRR, 2024

2023

Developing novel machine-learning-based fire weather indices.

Assaf Shmuel, Eyal Heifetz

Mach. Learn. Sci. Technol., March, 2023