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Found 8 papers, 0 papers with code
Randomized Confidence Bounds for Stochastic Partial Monitoring
In this paper, we consider the contextual and non-contextual PM settings with stochastic outcomes.
Successive Data Injection in Conditional Quantum GAN Applied to Time Series Anomaly Detection
In recent years, several quantum GAN architectures have been proposed in the literature.
MoP-CLIP: A Mixture of Prompt-Tuned CLIP Models for Domain Incremental Learning
Despite the recent progress in incremental learning, addressing catastrophic forgetting under distributional drift is still an open and important problem.
Causal Analysis for Robust Interpretability of Neural Networks
The result is task-specific causal explanatory graphs that can audit model behavior and express the actual causes underlying its performance.
DarSwin: Distortion Aware Radial Swin Transformer
Wide-angle lenses are commonly used in perception tasks requiring a large field of view.
FisheyeHDK: Hyperbolic Deformable Kernel Learning for Ultra-Wide Field-of-View Image Recognition
Some methods proposed the adaptation of CNNs to ultra-wide FoV images by learning deformable kernels.
Interventional Black-Box Explanations
Finally, we believe that our method is orthogonal to logic-based explanation methods and can be leveraged to improve their explanations.
Adaptable Deformable Convolutions for Semantic Segmentation of Fisheye Images in Autonomous Driving Systems
Finally, we provide an in-depth analysis of the effect of the deformable convolutions, bringing elements of discussion on the behavior of CNN models.
