Theory-based residual neural networks: A synergy of discrete choice models and deep neural networks
DOP: Deep Optimistic Planning with Approximate Value Function Evaluation
CryptoKnight:generating and modelling compiled cryptographic primitives
Deep learning and big data for intelligent transportation : enabling technologies and future trends
A CNN-Based Coherence-Driven Approach for InSAR Phase Unwrapping
Merging pruning and neuroevolution: towards robust and efficient controllers for modular soft robots
Robot-aided cloth classification using depth information and CNNs
Domain Adaption and Fusion for Domain-specific Traffic Sign Detection
Enhancing discrete choice models with representation learning
Uncertainty-Aware Attention Guided Sensor Fusion For Monocular Visual Inertial Odometry
Maximum Likelihood Uncertainty Estimation: Robustness to Outliers
Phi-Net: Deep Residual Learning for InSAR Parameters Estimation