What changes were proposed in this pull request? Added 2 noise layers for Keras: GaussianDropout, GaussianNoise, with unit tests, python wrapper, serializatoin test.. How was this patch tested? PR...
Alternative noising processes are also possible in continuous diffusion models, but as noted in the paper, only additive Gaussian noise has received significant attention. Autoregressive Models It's perhaps more interesting to compare VQ-Diffusion to AR models as they more frequently feature ...
openFrameworks addon for modeling a data distribution as a Gaussian mixture model Maintained by genekogan Last updated 8 years ago 4 Categories: Algorithms, Machine Learning ofxGNet Addon A general purpose, high level neural network ofxAddOn capable of modeling and mimicking arbitrary datasets with ea...
openGL image quad-wraper addon for OF. committed on 28 January, 2015 Merge branch 'experimental' jamesalliban ofxUIManager A parent class that allows me to quickly set up a ofxUI gui just the way I like it. committed on 28 January, 2015 Added quick (unfinished) example project bakercp...
尽管这类方法在许多领域的到了应用,然而这类方法的输出是观测变量间的因果关系,而忽略了隐变量间的因果关系。近期,研究学者利用适用于隐变量下新的“d-分离准则”,包括Low-rank条件,Generalized Independent Noise(GIN)条件等,给出了线性系统下隐变量...
3. **Gaussian blur**: Smooth out the texture to remove any remaining noise. 4. **Downsample**: Resize down to `texture_size` with LANCZOS resampling. ```python # Inpainting image_bgra = texture_buffer.copy() mask = (image_bgra[:, :, 3] == 0).astype(np.uint8) * 255 image_bgr...
"However, either the image or the noise timestep has not been provided." )if return_image_latents or (latents is None and not is_strength_max): image = image.to(device=device, dtype=dtype)if image.shape[1] == 4: image_latents = image ...
gaussian_gray_noise_prob=0.4, poisson_scale=[0.05, 3], poisson_gray_noise_prob=0.4, gaussian_sigma_step=0.1, poisson_scale_step=0.005), keys=['lq'], ), dict( type='RandomJPEGCompression', params=dict(quality=[30, 95], quality_step=3), keys=['lq'], ), dict( type='RandomVideoC...
latents (`Optional[torch.FloatTensor]`, defaults to `None`): Pre-generated noisy latents sampled from a Gaussian distribution, to be used as inputs for image generation. Can be used to tweak the same generation with different prompts. If not provided, a latents tensor is generated by sampl...
def create_gaussian_diffusion( *, steps=1000, learn_sigma=False, sigma_small=False, noise_schedule="linear", use_kl=False, predict_xstart=False, rescale_timesteps=False, rescale_learned_sigmas=False, timestep_respacing="", linear_start=0.0001, linear_end=0.02, ): betas = get_named_beta...