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Found 11 papers, 5 papers with code
Proto-MPC: An Encoder-Prototype-Decoder Approach for Quadrotor Control in Challenging Winds
Quadrotors are increasingly used in the evolving field of aerial robotics for their agility and mechanical simplicity.
ECLIPSE: A Resource-Efficient Text-to-Image Prior for Image Generations
The T2I prior model alone adds a billion parameters compared to the Latent Diffusion Models, which increases the computational and high-quality data requirements.
Adversarial Bayesian Augmentation for Single-Source Domain Generalization
Generalizing to unseen image domains is a challenging problem primarily due to the lack of diverse training data, inaccessible target data, and the large domain shift that may exist in many real-world settings.
WOUAF: Weight Modulation for User Attribution and Fingerprinting in Text-to-Image Diffusion Models
This paper introduces a novel approach to model fingerprinting that assigns responsibility for the generated images, thereby serving as a potential countermeasure to model misuse.
A New Super-Resolution Measurement of Perceptual Quality and Fidelity
Through a human subject study on super-resolution, we show that the proposed metric is highly correlated with the human perceptual quality, and better than most existing metrics.
$\mathcal{L}_1$Quad: $\mathcal{L}_1$ Adaptive Augmentation of Geometric Control for Agile Quadrotors with Performance Guarantees
Quadrotors that can operate safely in the presence of imperfect model knowledge and external disturbances are crucial in safety-critical applications.
SSR-GNNs: Stroke-based Sketch Representation with Graph Neural Networks
This paper follows cognitive studies to investigate a graph representation for sketches, where the information of strokes, i. e., parts of a sketch, are encoded on vertices and information of inter-stroke on edges.
$\mathcal{L}_1$ Adaptive Augmentation for Geometric Tracking Control of Quadrotors
This paper introduces an $\mathcal{L}_1$ adaptive control augmentation for geometric tracking control of quadrotors.
Data-Driven Learning of 3-Point Correlation Functions as Microstructure Representations
This paper considers the open challenge of identifying complete, concise, and explainable quantitative microstructure representations for disordered heterogeneous material systems.
Evaluating the Robustness of Bayesian Neural Networks Against Different Types of Attacks
To evaluate the robustness gain of Bayesian neural networks on image classification tasks, we perform input perturbations, and adversarial attacks to the state-of-the-art Bayesian neural networks, with a benchmark CNN model as reference.
An Optimality Gap Test for a Semidefinite Relaxation of a Quadratic Program with Two Quadratic Constraints
We propose a necessary and sufficient test to determine whether a solution for a general quadratic program with two quadratic constraints (QC2QP) can be computed from that of a specific convex semidefinite relaxation, in which case we say that there is no optimality gap.
Optimization and Control
