2 citations · 4 across the 8 of their papers we have counts for
11 papers
Hierarchical Gaussian Processes for Survey Weighting: Local Equivalent Weights in Structured Populations
Seonghun Lee
Regression-based survey weighting connects model-based population estimation with design-based inference through equivalent weights. For nonlinear models, equivalent weights can be…
ReLOBGen: Replayable Limit Order Book Message Generation
Junoh Kang, Kiseop Lee, Bohyung Han
We propose ReLOBGen, a method for generating limit order book (LOB) messages that are replayable by construction. Replayability is required for closed-loop market simulation, yet e…
D2PO: Optimizing Diffusion Samplers via Dynamic Preference
Jinkyu Kim, Jinyoung Choi, Bohyung Han
We propose D2PO (Dynamic Direct Preference Optimization), a principled framework for optimizing diffusion sampling policies with respect to timestep schedules and classifier-free g…
Probabilistic Signature Inversion: Learning Conditional Distributions from Truncated Signatures
Junoh Kang, Kiseop Lee, Bohyung Han
The signature transform is a principled feature map for continuous-time paths, valued for its uniqueness and universality. Recovering a path from its truncated signature is, howeve…
Score-Repellent Monte Carlo: Toward Efficient Non-Markovian Sampler with Constant Memory in General State Spaces
Jie Hu, Lingyun Chen, Geeho Kim +3
History-dependent sampling can reduce long-run Monte Carlo variance by discouraging redundant revisits, but existing schemes typically encode history through empirical measure on f…
ICM-SR: Image-Conditioned Manifold Regularization for Image Super-Resolution
Junoh Kang, Donghun Ryou, Bohyung Han
Real world image super-resolution (Real-ISR) often leverages the powerful generative priors of text-to-image diffusion models by regularizing the output to lie on their learned man…
STR-Match: Matching SpatioTemporal Relevance Score for Training-Free Video Editing
Junsung Lee, Junoh Kang, Bohyung Han
Previous text-guided video editing methods often suffer from temporal inconsistency, motion distortion, and-most notably-limited domain transformation. We attribute these limitatio…
Enhanced Diffusion Sampling via Extrapolation with Multiple ODE Solutions
Jinyoung Choi, Junoh Kang, Bohyung Han
Diffusion probabilistic models (DPMs), while effective in generating high-quality samples, often suffer from high computational costs due to their iterative sampling process. To ad…
FIFO-Diffusion: Generating Infinite Videos from Text without Training
Jihwan Kim, Junoh Kang, Jinyoung Choi +1
We propose a novel inference technique based on a pretrained diffusion model for text-conditional video generation. Our approach, called FIFO-Diffusion, is conceptually capable of…
A Training-Free Defense Framework for Robust Learned Image Compression
Myungseo Song, Jinyoung Choi, Bohyung Han
We study the robustness of learned image compression models against adversarial attacks and present a training-free defense technique based on simple image transform functions. Rec…
Observation-Guided Diffusion Probabilistic Models
Junoh Kang, Jinyoung Choi, Sungik Choi +1
We propose a novel diffusion-based image generation method called the observation-guided diffusion probabilistic model (OGDM), which effectively addresses the tradeoff between qual…