Cover Image

Distillation of Discrete Diffusion through Dimensional Correlations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hayakawa, Satoshi, Takida, Yuhta, Imaizumi, Masaaki, Wakaki, Hiromi, Mitsufuji, Yuki
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Numerical Analysis
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Theoretical Refinement of CLIP by Utilizing Linear Structure of Optimal Similarity
by: Yoshida, Naoki, et al.
Published: (2025)

Demystifying MaskGIT Sampler and Beyond: Adaptive Order Selection in Masked Diffusion
by: Hayakawa, Satoshi, et al.
Published: (2025)

$\textit{Jump Your Steps}$: Optimizing Sampling Schedule of Discrete Diffusion Models
by: Park, Yong-Hyun, et al.
Published: (2024)

Convex-Geometric Error Bounds for Positive-Weight Kernel Quadrature
by: Hayakawa, Satoshi
Published: (2026)

BigVSAN: Enhancing GAN-based Neural Vocoders with Slicing Adversarial Network
by: Shibuya, Takashi, et al.
Published: (2023)

SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer
by: Takida, Yuhta, et al.
Published: (2023)

SONA: Learning Conditional, Unconditional, and Mismatching-Aware Discriminator
by: Takida, Yuhta, et al.
Published: (2025)

Distill, Forget, Repeat: A Framework for Continual Unlearning in Text-to-Image Diffusion Models
by: George, Naveen, et al.
Published: (2025)

How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework
by: Ren, Yinuo, et al.
Published: (2024)

Efficiency without Compromise: CLIP-aided Text-to-Image GANs with Increased Diversity
by: Kobayashi, Yuya, et al.
Published: (2025)

Understanding and Accelerating the Training of Masked Diffusion Language Models
by: Hong, Chunsan, et al.
Published: (2026)

The Poisson Midpoint Method for Langevin Dynamics: Provably Efficient Discretization for Diffusion Models
by: Kandasamy, Saravanan, et al.
Published: (2024)

Transformed Low-rank Adaptation via Tensor Decomposition and Its Applications to Text-to-image Models
by: Tao, Zerui, et al.
Published: (2025)

Denoising Multi-Beta VAE: Representation Learning for Disentanglement and Generation
by: Uppal, Anshuk, et al.
Published: (2025)

G2D2: Gradient-Guided Discrete Diffusion for Inverse Problem Solving
by: Murata, Naoki, et al.
Published: (2024)

Discrete Differential Principle for Continuous Smooth Function Representation
by: Wang, Guoyou, et al.
Published: (2025)

Quantitative Approximation for Neural Operators in Nonlinear Parabolic Equations
by: Furuya, Takashi, et al.
Published: (2024)

Quantifying Correlations of Machine Learning Models
by: Li, Yuanyuan, et al.
Published: (2025)

Improving Classifier-Free Guidance in Masked Diffusion: Low-Dim Theoretical Insights with High-Dim Impact
by: Rojas, Kevin, et al.
Published: (2025)

Physics-informed Discretization-independent Deep Compositional Operator Network
by: Zhong, Weiheng, et al.
Published: (2024)

A Discrete Perspective Towards the Construction of Sparse Probabilistic Boolean Networks
by: Fok, Christopher H., et al.
Published: (2024)

Controlling Statistical, Discretization, and Truncation Errors in Learning Fourier Linear Operators
by: Subedi, Unique, et al.
Published: (2024)

Convolutional Surrogate for 3D Discrete Fracture-Matrix Tensor Upscaling
by: Špetlík, Martin, et al.
Published: (2026)

Approximation of Permutation Invariant Polynomials by Transformers: Efficient Construction in Column-Size
by: Takeshita, Naoki, et al.
Published: (2025)

ZNO: Stable Rational Neural Operators in the Z-Domain for Discrete-Time Dynamics
by: Zhu, Xianli, et al.
Published: (2026)

Temporal Difference Learning for High-Dimensional PIDEs with Jumps
by: Lu, Liwei, et al.
Published: (2023)

Improving Vector-Quantized Image Modeling with Latent Consistency-Matching Diffusion
by: Nguyen, Bac, et al.
Published: (2024)

ReBaNO: Reduced Basis Neural Operator Mitigating Generalization Gaps and Achieving Discretization Invariance
by: Zheng, Haolan, et al.
Published: (2025)

Finite Expression Method for Solving High-Dimensional Partial Differential Equations
by: Liang, Senwei, et al.
Published: (2022)

Neural Galerkin Schemes with Active Learning for High-Dimensional Evolution Equations
by: Bruna, Joan, et al.
Published: (2022)

Localized Diffusion Models
by: Gottwald, Georg A., et al.
Published: (2025)

Back-Projection Diffusion: Solving the Wideband Inverse Scattering Problem with Diffusion Models
by: Zhang, Borong, et al.
Published: (2024)

KD-PINN: Knowledge-Distilled PINNs for ultra-low-latency real-time neural PDE solvers
by: Bounja, Karim, et al.
Published: (2025)

A Discrete Neural Operator with Adaptive Sampling for Surrogate Modeling of Parametric Transient Darcy Flows in Porous Media
by: Chen, Zhenglong, et al.
Published: (2025)

VCT: Training Consistency Models with Variational Noise Coupling
by: Silvestri, Gianluigi, et al.
Published: (2025)

Solving High-Dimensional Partial Integral Differential Equations: The Finite Expression Method
by: Hardwick, Gareth, et al.
Published: (2024)

MAD: Manifold Attracted Diffusion
by: Elbrächter, Dennis, et al.
Published: (2025)

Stochastic Dimension Implicit Functional Projections for Exact Integral Conservation in High-Dimensional PINNs
by: Liang, Zhangyong
Published: (2026)

Adaptive-Distribution Randomized Neural Networks for PDEs: A Low-Dimensional Distribution-Learning Framework
by: Yang, You, et al.
Published: (2026)

Proposal-Guided Greedy Surrogate Refinement for PDE-Driven High-Dimensional Rare-Event Estimation
by: Gao, Zhiwei, et al.
Published: (2026)