:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Oden, Kevin D.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2602.17013
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Malliavin Calculus with Weak Derivatives for Counterfactual Stochastic Optimization
by: Krishnamurthy, Vikram, et al.
Published: (2025)

Conditioning Diffusions Using Malliavin Calculus
by: Pidstrigach, Jakiw, et al.
Published: (2025)

Malliavin Calculus for Score-based Diffusion Models
by: Mirafzali, Ehsan, et al.
Published: (2025)

Malliavin Calculus for Counterfactual Gradient Estimation in Adaptive Inverse Reinforcement Learning
by: Krishnamurthy, Vikram, et al.
Published: (2026)

Malliavin Calculus and Stochastic Differential Equations
by: Fang, Shizan, et al.
Published: (2025)

Malliavin Calculus for the one-dimensional Stochastic Stefan Problem
by: Antonopoulou, Dimitra C., et al.
Published: (2024)

A Malliavin calculus approach to score functions in diffusion generative models
by: Mirafzali, Ehsan, et al.
Published: (2025)

Malliavin Calculus for Degenerate Diffusions
by: Üstünel, Ali Süleyman
Published: (2020)

A Malliavin Calculus Approach to Backward Stochastic Volterra Integral Equations
by: Lei, Qian, et al.
Published: (2024)

Regression Trees Know Calculus
by: Wycoff, Nathan
Published: (2024)

Enhanced Dissipation via the Malliavin Calculus
by: Villringer, David
Published: (2024)

Malliavin Calculus for the stochastic heat equation and results on the density
by: Farazakis, D., et al.
Published: (2024)

When Analytic Calculus Cracks AdaBoost Code
by: Brossier, Jean-Marc, et al.
Published: (2023)

Malliavin Calculus for rough stochastic differential equations
by: Bugini, Fabio, et al.
Published: (2024)

Quantitative Fluctuation Analysis for Continuous-Time Stochastic Gradient Descent via Malliavin Calculus
by: Bourguin, Solesne, et al.
Published: (2026)

Matrix Calculus (for Machine Learning and Beyond)
by: Bright, Paige, et al.
Published: (2025)

The HR-Calculus: Enabling Information Processing with Quaternion Algebra
by: Mandic, Danilo P., et al.
Published: (2023)

Typing Tensor Calculus in 2-Categories (I)
by: Ahmadi, Fatimah Rita
Published: (2019)

Adapting to Stochastic and Adversarial Losses in Episodic MDPs with Aggregate Bandit Feedback
by: Ito, Shinji, et al.
Published: (2025)

Numerical Methods and Analysis via Random Field Based Malliavin Calculus for Backward Stochastic PDEs
by: Dai, Wanyang
Published: (2013)

Tempered Calculus for ML: Application to Hyperbolic Model Embedding
by: Nock, Richard, et al.
Published: (2024)

Perspectives on Stochastic Localization
by: Shi, Bobby, et al.
Published: (2025)

Functional Stochastic Localization
by: Gu, Anming, et al.
Published: (2026)

Cross-Entropy Optimization for Hyperparameter Optimization in Stochastic Gradient-based Approaches to Train Deep Neural Networks
by: Li, Kevin, et al.
Published: (2024)

Convergence Rate of the Last Iterate of Stochastic Proximal Algorithms
by: Vaidyan, Kevin Kurian Thomas, et al.
Published: (2026)

Halting Recurrent GNNs and the Graded $μ$-Calculus
by: Bollen, Jeroen, et al.
Published: (2025)

Revolutionizing Fractional Calculus with Neural Networks: Voronovskaya-Damasclin Theory for Next-Generation AI Systems
by: Santos, Rômulo Damasclin Chaves dos, et al.
Published: (2025)

On the Robustness of Deep Learning-predicted Contention Models for Network Calculus
by: Geyer, Fabien, et al.
Published: (2019)

Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND
by: Kang, Qiyu, et al.
Published: (2024)

The $\mathbf{Y}$-Combinator for LLMs: Solving Long-Context Rot with $λ$-Calculus
by: Roy, Amartya, et al.
Published: (2026)

Derivation of Back-propagation for Graph Convolutional Networks using Matrix Calculus and its Application to Explainable Artificial Intelligence
by: Hsiao, Yen-Che, et al.
Published: (2024)

Network Calculus with Flow Prolongation -- A Feedforward FIFO Analysis enabled by ML
by: Geyer, Fabien, et al.
Published: (2022)

Notes on Forré's Notion of Conditional Independence and Causal Calculus for Continuous Variables
by: Chen, Leihao
Published: (2026)

Stochastic Variational Inference with Tuneable Stochastic Annealing
by: Paisley, John, et al.
Published: (2025)

Closing the Computational-Query Depth Gap in Parallel Stochastic Convex Optimization
by: Jambulapati, Arun, et al.
Published: (2024)

A Malliavin-Gamma calculus approach to Score Based Diffusion Generative models for random fields
by: Greco, Giacomo
Published: (2025)

Private Stochastic Convex Optimization with Heavy Tails: Near-Optimality from Simple Reductions
by: Asi, Hilal, et al.
Published: (2024)

Weyl Calculus and Exactly Solvable Schrödinger Bridges with Quadratic State Cost
by: Teter, Alexis M. H., et al.
Published: (2024)

Latent Stochastic Interpolants
by: Singh, Saurabh, et al.
Published: (2025)

Training-Free Generation of Protein Sequences from Small Family Alignments via Stochastic Attention
by: Varner, Jeffrey D.
Published: (2026)