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🏛️ The Neural & Evolutionary Crypt
cs.NE: Where Neural & Evolutionary papers rest without their code.
6370
Total Papers
5604
No Code
153
Twilight
613
Has Code
9.6%
Survival Rate
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A Universal Flexible Neuromorphic Tactile System with Multithreshold Strategy
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Neuromorphic Keyword Spotting with Pulse Density Modulation MEMS Microphones
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Synaptic Modulation using Interspike Intervals Increases Energy Efficiency of Spiking Neural Networks
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Using CSNNs to Perform Event-based Data Processing & Classification on ASL-DVS
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Efficient Multi-Objective Neural Architecture Search via Pareto Dominance-based Novelty Search
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Crafting Generative Art through Genetic Improvement: Managing Creative Outputs in Diverse Fitness Landscapes
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Learning mental states estimation through self-observation: a developmental synergy between intentions and beliefs representations in a deep-learning model of Theory of Mind
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Lexicase Selection Parameter Analysis: Varying Population Size and Test Case Redundancy with Diagnostic Metrics
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Online Pseudo-Zeroth-Order Training of Neuromorphic Spiking Neural Networks
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Sliding Window Bi-Objective Evolutionary Algorithms for Optimizing Chance-Constrained Monotone Submodular Functions
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Local Optima in Diversity Optimization: Non-trivial Offspring Population is Essential
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Evaluating Deep Neural Networks in Deployment (A Comparative and Replicability Study)
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Hybridizing Target- and SHAP-encoded Features for Algorithm Selection in Mixed-variable Black-box Optimization
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A Two-stage Evolutionary Framework For Multi-objective Optimization
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Artificial Intelligence Based Navigation in Quasi Structured Environment
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Advanced Artificial Intelligence Strategy for Optimizing Urban Rail Network Design using Nature-Inspired Algorithms
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Natively neuromorphic LMU architecture for encoding-free SNN-based HAR on commercial edge devices
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Parameter Tuning of the Firefly Algorithm by Standard Monte Carlo and Quasi-Monte Carlo Methods
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Multi-objective Binary Differential Approach with Parameter Tuning for Discovering Business Process Models: MoD-ProM
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Evolution of Rewards for Food and Motor Action by Simulating Birth and Death
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Online Training of Hopfield Networks using Predictive Coding
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Brain-inspired Computational Modeling of Action Recognition with Recurrent Spiking Neural Networks Equipped with Reinforcement Delay Learning
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