在训练时,使用selfcondition策略提升模型性能。 在训练时,采用mse loss比fape loss效果更好。 对于各种下游任务进行巧妙的训练数据集的构造:酶活性位点,功能位点数据的构造,对接数据是否也能设计出训练数据集。 在进行蛋白质结合剂设计的时候,通过在二维信息上的mask策略,使得最终在结合剂设计时,可以依据想要的二级结构...
self-condition:采样时将每次估计出的x_0也作为下次采样的条件输入。动机是传统DDPM流程中上一步的x_0被直接丢弃,当前步的去噪完全没有参考上一步的x_0。实现方式就是把上一步的x_0和当前的x_t直接concat,但只有50%概率做self-condition,另外50%概率将上一步的x_0直接置0输入。整体感觉是个实验trick,但验...
LDM(Latent Diffusion Models) 通过在模型架构中引入 cross-attention(交叉注意力层) 来实现多模态训练，使得 Diffusion model 可以更灵活地实现对 class-condition, text-to-image, layout-to-image 的支持。然而 cross-attention 层对比原始 Diffusion model 的 CNN 层增加了额外的计算开销，极大增加了训练成本。Colo...
Here, we introduce the self-consistent boundary condition for the truncated boundary into this calculation. This reduces the effect of the boundary on the results, showing that the self-consistent boundary condition is useful for calculations for analyzing optical topographic images.关键词:...
inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(c_crossattn, image_cond_in[a:b])) File "E:\sd-webui-aki\sd-webui-aki-v4\py310\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "E:\sd-...
In this way, the model is discouraged from focusing on minor details and self-conditioning [36], which conditions the denoising process based on the previous estimate of the recovered sample 𝑥˜0x˜0. All the evaluated models are trained for 1 million steps with a batch size of 64 on...
in which the model can condition on previous predictions between timesteps (Fig.1a, bottom row andSupplementary Methods). The latter strategy was inspired by the success of ‘recycling’ in AF2, which is also central to the more recent RF model used here (Supplementary Methods). Self-condition...
Fig. 14. Self-diffusion coefficients of CO2 in UiO-66, UiO-67 and UiO-68 at 298 K. Show moreView article Related terms: Energy Engineering Computational Fluid Dynamics Turbulent Diffusion Diffusion Coefficient Boundary Condition Energy Equation Momentum Equation Advection Convective Fluid Viscosity View...
在classifier-free guidance model 中,没有利用 classifier,而是同时训练了condition model 和 unconditional model,而且使用同一个网络来实现,只需要需要输入信息中的类别信息即可,在生成过程中,则通过调整两种模型的 score 的权重来在多样性(FID)和真实度(IS)中权衡取舍。
For this reason, we add a shape latent variable as the condition for the transition kernel. When generating point clouds, the shape latent variable has a prior distribution that we parameterize with normalizing flows for high model flexibility. When auto-encoding point clouds, the shape latent ...