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Found 10 papers, 1 papers with code
ConFL: Constraint-guided Fuzzing for Machine Learning Framework
Guided by the constraints, ConFL is able to generate valid inputs that can pass the verification and explore deeper paths of kernel codes.
Mid-level Representation Enhancement and Graph Embedded Uncertainty Suppressing for Facial Expression Recognition
On the other hand, GUS is introduced to suppress the feature ambiguity in the representation space.
Facial Expression Recognition
Facial Expression Recognition (FER)
+1
Segmentation-free PVC for Cardiac SPECT using a Densely-connected Multi-dimensional Dynamic Network
In this work, we develop a deep-learning-based method for fast cardiac SPECT PVC without anatomical information and associated organ segmentation.
Frequency-based tension assessment of an inclined cable with complex boundary conditions using the PSO algorithm
However, the calculation formulas for the conventional frequency-based method are generally based on the ideally hinged or fixed boundary conditions without a comprehensive consideration of the inclination angle, sag-extensibility, and flexural stiffness of cables, leading to a significant error in cable tension identification.
Boosting Offline Reinforcement Learning with Residual Generative Modeling
While most research focuses on the state-action function part through reducing the bootstrapping error in value function approximation induced by the distribution shift of training data, the effects of error propagation in generative modeling have been neglected.
Towards Playing Full MOBA Games with Deep Reinforcement Learning
However, existing work falls short in handling the raw game complexity caused by the explosion of agent combinations, i. e., lineups, when expanding the hero pool in case that OpenAI's Dota AI limits the play to a pool of only 17 heroes.
Deep Generative Modeling for Mechanistic-based Learning and Design of Metamaterial Systems
For microstructure design, the tuning of mechanical properties and complex manipulations of microstructures are easily achieved by simple vector operations in the latent space.
Mastering Complex Control in MOBA Games with Deep Reinforcement Learning
We study the reinforcement learning problem of complex action control in the Multi-player Online Battle Arena (MOBA) 1v1 games.
Similarity Grouping-Guided Neural Network Modeling for Maritime Time Series Prediction
Reliable and accurate prediction of time series plays a crucial role in maritime industry, such as economic investment, transportation planning, port planning and design, etc.
Learning-based Regularization for Cardiac Strain Analysis with Ability for Domain Adaptation
We extended this framework to include a supervised loss term on synthetic data and showed the effects of biomechanical constraints on the network's ability for domain adaptation.
