1 citations · 2 across the 8 of their papers we have counts for
8 papers
Value Gradient Sampler: Learning Invariant Value Functions for Equivariant Diffusion Sampling
Himchan Hwang, Hyeokju Jeong, Dong Kyu Shin +4
We propose the Value Gradient Sampler (VGS), a diffusion sampler parameterized by value functions. VGS generates samples from an unnormalized target density (i.e., energy) by evolv…
Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models
Sangwoong Yoon, Himchan Hwang, Dohyun Kwon +2
We present a maximum entropy inverse reinforcement learning (IRL) approach for improving the sample quality of diffusion generative models, especially when the number of generation…
Generalized Contrastive Divergence: Joint Training of Energy-Based Model and Diffusion Model through Inverse Reinforcement Learning
Sangwoong Yoon, Dohyun Kwon, Himchan Hwang +2
We present Generalized Contrastive Divergence (GCD), a novel objective function for training an energy-based model (EBM) and a sampler simultaneously. GCD generalizes Contrastive D…
Variational Weighting for Kernel Density Ratios
Sangwoong Yoon, Frank C. Park, Gunsu S Yun +2
Kernel density estimation (KDE) is integral to a range of generative and discriminative tasks in machine learning. Drawing upon tools from the multidimensional calculus of variatio…
Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach
Sangwoong Yoon, Young-Uk Jin, Yung-Kyun Noh +1
We present a new method of training energy-based models (EBMs) for anomaly detection that leverages low-dimensional structures within data. The proposed algorithm, Manifold Project…
Evaluating Out-of-Distribution Detectors Through Adversarial Generation of Outliers
Sangwoong Yoon, Jinwon Choi, Yonghyeon Lee +2
A reliable evaluation method is essential for building a robust out-of-distribution (OOD) detector. Current robustness evaluation protocols for OOD detectors rely on injecting pert…
Autoencoding Under Normalization Constraints
Sangwoong Yoon, Yung-Kyun Noh, Frank Chongwoo Park
Likelihood is a standard estimate for outlier detection. The specific role of the normalization constraint is to ensure that the out-of-distribution (OOD) regime has a small likeli…
Image-to-Image Retrieval by Learning Similarity between Scene Graphs
Sangwoong Yoon, Woo Young Kang, Sungwook Jeon +4
As a scene graph compactly summarizes the high-level content of an image in a structured and symbolic manner, the similarity between scene graphs of two images reflects the relevan…