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Found 8 papers, 4 papers with code
MoMA: Multimodal LLM Adapter for Fast Personalized Image Generation
This approach effectively synergizes reference image and text prompt information to produce valuable image features, facilitating an image diffusion model.
MagicPose: Realistic Human Poses and Facial Expressions Retargeting with Identity-aware Diffusion
In this work, we propose MagicPose, a diffusion-based model for 2D human pose and facial expression retargeting.
Do We Really Need to Learn Representations from In-domain Data for Outlier Detection?
Unsupervised outlier detection, which predicts if a test sample is an outlier or not using only the information from unlabelled inlier data, is an important but challenging task.
EBMs Trained with Maximum Likelihood are Generator Models Trained with a Self-adverserial Loss
Doing so allows us to study the density induced by the dynamics (if the dynamics are invertible), and connect with GANs by treating the dynamics as generator models, the initial values as latent variables and the loss as optimizing a critic defined by the very same energy that determines the generator through its gradient.
Exponential Tilting of Generative Models: Improving Sample Quality by Training and Sampling from Latent Energy
In this paper, we present a general method that can improve the sample quality of pre-trained likelihood based generative models.
Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder
An important application of generative modeling should be the ability to detect out-of-distribution (OOD) samples by setting a threshold on the likelihood.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
A Method to Model Conditional Distributions with Normalizing Flows
In particular, we use our proposed method to analyze inverse problems with invertible neural networks by maximizing the posterior likelihood.
Generative Latent Flow
In this work, we propose the Generative Latent Flow (GLF), an algorithm for generative modeling of the data distribution.
Ranked #1 on
Image Generation
on Fashion-MNIST
