2021.7.26 Neural papers

 

07-21-2021

Multi-Stream Transformers
by Mikhail Burtsev et al

07-20-2021

Into Summarization Techniques for IoT Data Discovery Routing
by Hieu Tran et al

07-21-2021

Learning Theorem Proving Components
by Karel Chvalovský et al

07-21-2021

Differentiable Feature Selection, a Reparameterization Approach
by Jérémie Dona et al

07-21-2021

Shedding some light on Light Up with Artificial Intelligence
by Libo Sun et al

07-21-2021

How to Tell Deep Neural Networks What We Know
by Tirtharaj Dash et al

07-20-2021

Evolutionary Innovation Viewed as Novel Physical Phenomena and Hierarchical Systems Building
by Tim Taylor

07-20-2021

An Exploration of Exploration: Measuring the ability of lexicase selection to find obscure pathways to optimality
by Jose Guadalupe Hernandez et al

07-21-2021

A Multi-objective Evolutionary Algorithm for EEG Inverse Problem
by José Enrique Alvarez Iglesias et al

07-22-2021

Generating Large-scale Dynamic Optimization Problem Instances Using the Generalized Moving Peaks Benchmark
by Mohammad Nabi Omidvar et al

07-23-2021

Applying Evolutionary Algorithms Successfully: A Guide Gained from Real-world Applications
by Wilfried Jakob

07-20-2021

Using Shape Constraints for Improving Symbolic Regression Models
by Christian Haider et al

07-20-2021

LENS: Layer Distribution Enabled Neural Architecture Search in Edge-Cloud Hierarchies
by Mohanad Odema et al

07-22-2021

Hash-Based Tree Similarity and Simplification in Genetic Programming for Symbolic Regression
by Bogdan Burlacu et al

07-20-2021

ECG Heartbeat Classification Using Multimodal Fusion
by Zeeshan Ahmad et al

07-20-2021

An Efficient Multi-objective Evolutionary Approach for Solving the Operation of Multi-Reservoir System Scheduling in Hydro-Power Plants
by C. G. Marcelino et al

 
Craig Smith