Search Results for author:
Found 7 papers, 1 papers with code
Semi-Supervised Learning for Dose Prediction in Targeted Radionuclide: A Synthetic Data Study
The aim is to develop an approach that achieves accurate results when PET/CT images are available, but are associated with only a few post-therapy dosimetry data provided by SPECT images.
UV-IDM: Identity-Conditioned Latent Diffusion Model for Face UV-Texture Generation
To solve these problems we introduce an Identity-Conditioned Latent Diffusion Model for face UV-texture generation (UV-IDM) to generate photo-realistic textures based on the Basel Face Model (BFM).
Prompt Tuning Inversion for Text-Driven Image Editing Using Diffusion Models
This technique ensures a superior trade-off between editability and high fidelity to the input image of our method.
Rethinking the Number of Shots in Robust Model-Agnostic Meta-Learning
Based on this observation, we propose a simple strategy, i. e., increasing the number of training shots, to mitigate the loss of intrinsic dimension caused by robustness-promoting regularization.
Associative Adversarial Learning Based on Selective Attack
We show that our method improves the recognition accuracy of adversarial training on ImageNet by 8. 32% compared with the baseline.
IDARTS: Interactive Differentiable Architecture Search
Differentiable Architecture Search (DARTS) improves the efficiency of architecture search by learning the architecture and network parameters end-to-end.
