Our implementation is based on the ED-DPM, Guided-diffusion, dpm-solver.CitationIf you find our paper or codebase useful, please consider citing us as:@article{zhang2023domain, title = {Domain-guided conditional diffusion model for unsupervised domain adaptation}, author = {Yulong Zhang and ...
I.I. contributed to the main idea, conceptualization, code and manuscript writing. H.S. contributed to the main idea, code reorganization and docking experiments. C.V. contributed to the mathematical conceptualization of the 3D conditional diffusion model and manuscript writing. A.S. contributed to...
Transfer learning is crucial in training deep neural networks on new target tasks. Current transfer learning methods always assume at least one of (i) Sour
(version="stabilityai/stable-diffusion-xl-base-1.0",# from HF Hubtext_embedder_subfolder="text_encoder_2",tokenizer_subfolder="tokenizer_2",input_key="text",always_return_pooled=True,# Return a 1-dimensional tensor)embeddder_1=ClipEmbedder(config=embedder_1_config)# Embedder acting on a ...
the forward diffusion process can be performed with a single step diffu- sion as follows: \label {eq:forward_sde} \x _{N'} = a_{N'}\x _{0}+b_{N'}\z (12) where z ∼ N (0, I), and aN′ , bN′ for SMLD and D...
Code availability section The source code is available on github.com/ML4ITS/Latent-Diffusion-Model-for-Conditional-Reservoir-Facies-Generation Contact: daesoo.lee@ntnu.no Hardware requirements: a sufficient GPU device for training a deep learning model with the PyTorch library. We used a single NVI...
Random forest based variable importance measures have become popular tools for assessing the contributions of the predictor variables in a fitted random forest. In this article we reconsider a frequently used variable importance measure, the Conditional
Figure 4. Proposed model structure. 2.2.2. Low-Rank Adaptation of Stable Diffusion Model To address the conceptual bias in the stable-diffusion-v1-5 base model, this paper introduces Low-Rank Adaptation (LoRA) to incorporate dataset-specific image features into the pre-trained weights. LoRA ...
Code availability The code for cG-SchNet is available atwww.github.com/atomistic-machine-learning/cG-SchNet(DOI 10.5281/zenodo.590702771). This includes the routines for training and deploying the model, for filtering generated structures, all hyper-parameter settings used in our experiments, and the...
Code availability The scripts used to produce these results as well as training data are available at10.24433/CO.6650973.v161. The finite-element source codes used to generate the training, validation and testing data are available athttps://github.com/teeratornk/jcp_YJCPH_110030_git, and a...