Multiplicative Gamma Noise

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4 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

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Gumbel Straight Flow: Distilling Autoregressive Models into One-step Flow Maps
Sep 30, 2026Yeongmin Kim, Arnaud Doucet, Andrew Campbell +3Flow Map Autoregressive Language Models
Google DeepMind · Work done as a Student Researcher at Google DeepMind Amsterdam
Beyond Noise: Understanding and Overcoming Temperature Effects in Analog DNN Inference
Sep 14, 2026Niklas Summ, Xiao Wang, Hendrik Borras +2Neural Network Inference Hardware-Aware
Hardware and Artificial Intelligence Lab, Institute of Computer Engineering, Heidelberg University, Germany
Almost Sure Convergence Analysis of Stochastic Gradient Methods with Clipping and Additive Noise
Sep 10, 2026Amartya Mukherjee, Jun LiuStochastic Gradient Descent Gradient Clipping
Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1
Poisson Image Denoising Using Minimax Concave and Reweighted $\ell_1$ Penalties: Nonblind and Blind Approaches
Sep 7, 2026Reza ParvazGaussian Deblurring Image Restoration
aDepartment of Engineering Sciences, Faculty of Advanced Technologies,Sep University of Mohaghegh Ardabili, Ardabil, Iran
Can Scene Text Recognition Read Rare Compositions?
Sep 1, 2026Genpei ZhangScene Text Recognition Character Error Rate
University of Wisconsin–Madison
Sparse and robust geometric twin support vector machine via asymmetric RoBoSS loss function
Aug 12, 2026Kai Qi, Xinji Huang, Hongchun WangSupport Vector Machines Loss Function
National Center for Applied Mathematics in Chongqing, Chongqing Normal University, Chongqing, 401331, China. · School of Mathematical Sciences, Chongqing Normal University, Chongqing, 401331, China.
A geometry-based deep equilibrium model for image restoration under multiplicative Gamma noise
Aug 5, 2026Shengkun Yang, Luca Ratti, Zhichang GuoImage Restoration Multiplicative Gamma Noise
School of Mathematics, Harbin Institute of Technology, Harbin, 150001, Heilongjiang, China. · Department of Mathematics, University of Bologna, Bologna, 40126, Emilia-Romagna, Italy.
Upper-Expectile Multi-Step Q-Learning for Off-Policy Reinforcement Learning
Aug 3, 2026Abdelghani Ghanem, Mounir GhoghoQ-Learning Value Functions
College of Computing Mohammed VI Polytechnic University Rabat 11103, Morocco
Orca: Neural Operators for Causal Reasoning in Continuous Time
Jul 30, 2026Gerrit Großmann, David A. Selby, Sebastian J. VollmerCausal Reasoning Neural Operators
German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany
$γ$ -Bridge: A Look-Parametric Diffusion Bridge
Jul 21, 2026Xuran Hu, Yujie Zhu, Tengxi Wang +2Diffusion Bridges Multiplicative Gamma Noise
Urban Governance and Design Thrust, Society Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China · Faculty of Science and Engineering, Macquarie University, NSW 2109, Sydney, Australia · School of Geography and Planning, Ningxia University, Yinchuan, China
Design Choices in Splitting-Based Self-Supervised Sparse-View CT Reconstruction
Jul 12, 2026Nadja Gruber, Lukas Neumann, Ander Biguri +3Sparse-View Partitioning
Department of Computer Science, University of Innsbruck, Austria. · Institute of Basic Sciences in Engineering Science, University of Innsbruck, Austria. · Department of Applied Mathematics and Theoretical Physics, University of Cambridge, UK. +3
Denoising ICF Images with Multiplicative Uniform Noise: A Self-Supervised Study Based on the Log-Domain Noisier2Inverse Framework
Jun 26, 2026Gyeongha Hwang, Bradley Thomas Wolfe, Naima NaheedMultiplicative Gamma Noise Gaussian Noise
Department of Mathematics, Yeungnam University, Gyeongsan, Republic of Korea. · Research Technologist, P-4: Thermonuclear Plasma Physics, Los Alamos National Laboratory, Los Alamos, NM 87545, USA. · Department of Computer Science and Engineering, Benedict College, Columbia, SC 29204, USA.
Beyond Additivity: Causal Discovery in Location-Scale Noise Models with Hidden Variables
Jun 6, 2026Mariyam Khan, Shohei Shimizu, Thong PhamCausal Discovery Methods Causal
University of Bergen · *Work conducted while a student trainee at RIKEN AIP · 2The University of Osaka +2
Local Differential Privacy with Correlated Noise Achieves Central-DP Optimal Cost
May 28, 2026Madhura Pathegama, Srikanth Avasarala, Viveck R. Cadambe +1Privacy Multiplicative Gamma Noise
Georgia Institute of Technology, Atlanta, GA, USA
Mind the Gap: Mixtures of Gaussians in Approximate Differential Privacy
May 27, 2026Huikang Liu, Aras Selvi, Wolfram WiesemannStandard Differential-Privacy Δ)$-Differential Privacy
1Shanghai Jiao Tong University · 2UCL School of Management · 3Imperial Business School
Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity
May 26, 2026Jakub Wornbard, Zikai Shen, Dimitri Meunier +1Heteroskedasticity Multiplicative Gamma Noise
University College London
Gumbel Machine: Counterfactual Student Writing Generation via Gumbel Noise Steering
May 26, 2026Hunter McNichols, Alexander Scarlatos, Mihai Dascalu +2Random Multiplicative Gamma Noise
University of Massachusetts Amherst · University Politehnica of Bucharest · Arizona State University
Flowing with Confidence
May 18, 2026Friso de Kruiff, Dario Coscia, Max Welling +1Generative Models Confidence Calibration
CuspAI · AMLab, University of Amsterdam · mathLab, SISSA
Beyond Bounded Variance: Variance-Reduced Normalized Methods for Nonconvex Optimization under Blum-Gladyshev Noise
May 14, 2026Antesh Upadhyay, Arda Fazla, Abolfazl HashemiStochastic Convex Optimization Stochastic Gradient Descent
School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA.
SurF: A Generative Model for Multivariate Irregular Time Series Forecasting
May 13, 2026Mohammad R. Rezaei, Tejas Balaji, Rahul G. KrishnanTime-Series Generation Determinantal Point Process
Department of Computer Science University of Toronto Vector Institute Toronto, ON, Canada
Learning-based Statistical Refinement for Denoising
May 5, 2026Rihuan KeIterative Denoising Methods Multiplicative Gamma Noise
School of Mathematics, University of Bristol, BS8 1QU Bristol, U.K.
Skewness-Robust Causal Discovery in Location-Scale Noise Models
Nov 18, 2025Daniel Klippert, Alexander MarxCausal Discovery Methods Skewness
Department of Statistics, TU Dortmund University, Germany · Research Center Trustworthy Data Science and Security, University Alliance Ruhr, Germany.
Better Convergence Guarantees for Sign-Based Momentum Methods
Jul 16, 2025Wei Jiang, Dingzhi Yu, Sifan Yang +3Momentum Stochastic Gradient Descent Convergence
National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China · School of Artificial Intelligence, Nanjing University, Nanjing, China
A Tunable Despeckling Neural Network Stabilized via Diffusion Equation
Nov 24, 2024Yi Ran, Zhichang Guo, Jia Li +3Iterative Denoising Methods Synthetic Aperture Radar
School of Mathematics, Harbin Institute of Technology, 150001 Harbin, China · Helmholtz Imaging, Deutsches Elektronen-Synchrotron DESY, 22607 Hamburg, Germany · Fachbereich Mathematik, Universität Hamburg, 20146 Hamburg, Germany
Deep learning based numerical approximation algorithms for stochastic partial differential equations
Dec 2, 2020Christian Beck, Sebastian Becker, Patrick Cheridito +2Stochastic Differential Equations Neural Approximations
Department of Mathematics, ETH Zurich · School of Data Science and School of Artificial Intelligence,2025 The Chinese University of Hong Kong, Shenzhen (CUHK-Shenhen) · Applied Mathematics: Institute for Analysis and Numerics, University of Münster +1

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Gumbel Straight Flow: Distilling Autoregressive Models into One-step Flow Maps

Yeongmin Kim, Arnaud Doucet, Andrew Campbell, Valentin De Bortoli+2

Google DeepMind · Work done as a Student Researcher at Google DeepMind Amsterdam

Flow Map Autoregressive Language Models Autoregressive Model Large Language Model Baselines Multiplicative Gamma Noise

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We present Gumbel Straight Flow (GSF), a continuous flow map language model that leverages the noise-data coupling of a pretrained autoregressive language (AR) model. We theoretically demonstrate that the coupling between Gumbel noise and one-hot token sequences induced by an autoregressive model yields non-intersecting linear paths connecting the noise to the sequence representations. To further enhance high-quality few-step path sampling, we use a flow map semigroup objective where the tangent (velocity) condition is guided directly by the AR teacher. Across various benchmarks, including pretraining and downstream tasks, GSF can outperform current few-step language generation baselines.

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