1 citations · 1 across the 2 of their papers we have counts for
5 papers
Improving the adaptive and continuous learning capabilities of artificial neural networks: Lessons from multi-neuromodulatory dynamics
Jie Mei, Alejandro Rodriguez-Garcia, Daigo Takeuchi +4
Continuous, adaptive learning, the ability to adapt to the environment and keep improving performance, is a hallmark of natural intelligence. Biological organisms excel in acquirin…
A Graph Neural Network Approach for Localized and High-Resolution Temperature Forecasting
Joud El-Shawa, Elham Bagheri, Sedef Akinli Kocak +1
Heatwaves are intensifying worldwide and are among the deadliest weather disasters. The burden falls disproportionately on marginalized populations and the Global South, where unde…
Semi-Supervised Anomaly Detection in Brain MRI Using a Domain-Agnostic Deep Reinforcement Learning Approach
Zeduo Zhang, Yalda Mohsenzadeh
To develop a domain-agnostic, semi-supervised anomaly detection framework that integrates deep reinforcement learning (DRL) to address challenges such as large-scale data, overfitt…
Modeling Visual Memorability Assessment with Autoencoders Reveals Characteristics of Memorable Images
Elham Bagheri, Yalda Mohsenzadeh
Image memorability refers to the phenomenon where certain images are more likely to be remembered than others. It is a quantifiable and intrinsic image attribute, defined as the li…
Efficient Slice Anomaly Detection Network for 3D Brain MRI Volume
Zeduo Zhang, Yalda Mohsenzadeh
Current anomaly detection methods excel with benchmark industrial data but struggle with natural images and medical data due to varying definitions of 'normal' and 'abnormal.' This…