Counterfactual explanations have shown promising results as a post-hoc framework to make image classifiers more explainable. In this paper, we propose DiME, method allowing the generation of counterfactual images using recent diffusion models. By leveraging guided generative process, our proposed methodology shows how use gradients target classifier generate input instances. Further, analyze cu...

Diffusion models have emerged as a powerful generative method for synthesizing high-quality and diverse set of images. In this paper, we propose video generation based on diffusion models, where the effects motion are modeled in an implicit condition manner, i.e. one can sample plausible motions according to latent feature frames. We improve quality generated videos by proposing multiple strate...

one and two dimensional contaminant transport by pure diffusion through single layer of fine grained soil was investigated using one and two dimensional laboratory models. these models simulates a simple hydrogeologic situation underneath a solid waste landfill comprising a fine grained soil overlying a bed rock. sodium chloride solution was sued as a contaminant source above a compacted clayey...

the option-pricing problem is always an important part in modern finance. assuming that the stock diffusion is a constant, some literature has introduced many stock models and given corresponding option pricing formulas within the framework of the uncertainty theory. in this paper, we propose a new stock model with uncertain stock diffusion for uncertain markets. some option pricing formulas on...