65 citations · 94 across the 6 of their papers we have counts for
6 papers
Plug-and-Play Diffusion Distillation
Yi-Ting Hsiao, Siavash Khodadadeh, Kevin Duarte +4
Diffusion models have shown tremendous results in image generation. However, due to the iterative nature of the diffusion process and its reliance on classifier-free guidance, infe…
Guided Co-Modulated GAN for 360° Field of View Extrapolation
Mohammad Reza Karimi Dastjerdi, Yannick Hold-Geoffroy, Jonathan Eisenmann +2
We propose a method to extrapolate a 360° field of view from a single image that allows for user-controlled synthesis of the out-painted content. To do so, we propose improvements…
Predicting infections in the Covid-19 pandemic -- lessons learned
Sharare Zehtabian, Siavash Khodadadeh, Damla Turgut +1
Throughout the Covid-19 pandemic, a significant amount of effort had been put into developing techniques that predict the number of infections under various assumptions about the p…
Privacy-Preserving Learning of Human Activity Predictors in Smart Environments
Sharare Zehtabian, Siavash Khodadadeh, Ladislau Bölöni +1
The daily activities performed by a disabled or elderly person can be monitored by a smart environment, and the acquired data can be used to learn a predictive model of user behavi…
Unsupervised Meta-Learning through Latent-Space Interpolation in Generative Models
Siavash Khodadadeh, Sharare Zehtabian, Saeed Vahidian +3
Unsupervised meta-learning approaches rely on synthetic meta-tasks that are created using techniques such as random selection, clustering and/or augmentation. Unfortunately, cluste…
Unsupervised Meta-Learning For Few-Shot Image Classification
Siavash Khodadadeh, Ladislau Bölöni, Mubarak Shah
Few-shot or one-shot learning of classifiers requires a significant inductive bias towards the type of task to be learned. One way to acquire this is by meta-learning on tasks simi…