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Found 5 papers, 0 papers with code
Adapting to Covariate Shift in Real-time by Encoding Trees with Motion Equations
In this paper, we demonstrated how a neural network integrated with Xenovert achieved better results in 4 out of 5 shifted datasets, saving the hurdle of retraining a machine learning model.
Synthetic Shifts to Initial Seed Vector Exposes the Brittle Nature of Latent-Based Diffusion Models
To understand the impact of the initial seed vector on generated samples, we propose a reliability evaluation framework that evaluates the generated samples of a diffusion model when the initial seed vector is subjected to various synthetic shifts.
The Challenges of Image Generation Models in Generating Multi-Component Images
Recent advances in text-to-image generators have led to substantial capabilities in image generation.
Generating Oscillation Activity with Echo State Network to Mimic the Behavior of a Simple Central Pattern Generator
However, we find that a reservoir that develops oscillatory activity without any external excitation can mimic the behaviour of a simple CPG in biological systems.
Dynamical Equations With Bottom-up Self-Organizing Properties Learn Accurate Dynamical Hierarchies Without Any Loss Function
The hurdle is that general patterns are difficult to define in terms of dynamical equations and designing a system that could learn by reordering itself is still to be seen.
