Imagen de Portada

Neural Expectation Operators

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Qi, Qian
Formato:	Preprint
Publicado:	2025
Materias:	Probability Artificial Intelligence Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A Unified Theory of $θ$-Expectations
por: Qi, Qian
Publicado: (2025)

A Mean-Field Theory of $Θ$-Expectations
por: Qi, Qian
Publicado: (2025)

Neural Brownian Motion
por: Qi, Qian
Publicado: (2025)

Quantitative CLTs in Deep Neural Networks
por: Favaro, Stefano, et al.
Publicado: (2023)

Neural Laplace for learning Stochastic Differential Equations
por: Carrel, Adrien
Publicado: (2024)

Feature Learning Dynamics in Infinite-Depth Neural Networks
por: Yao, Zihan, et al.
Publicado: (2025)

Neural Network Parameter-optimization of Gaussian pmDAGs
por: Saremi, Mehrzad
Publicado: (2023)

Efficient Training of Neural SDEs Using Stochastic Optimal Control
por: Daems, Rembert, et al.
Publicado: (2025)

Explicit Density Approximation for Neural Implicit Samplers Using a Bernstein-Based Convex Divergence
por: de Frutos, José Manuel, et al.
Publicado: (2025)

Learning Chaotic Systems and Long-Term Predictions with Neural Jump ODEs
por: Krach, Florian, et al.
Publicado: (2024)

Causal Effect Identification in Heterogeneous Environments from Higher-Order Moments
por: Kivva, Yaroslav, et al.
Publicado: (2025)

Nonparametric Identification of Latent Concepts
por: Zheng, Yujia, et al.
Publicado: (2025)

Greedy Selection under Independent Increments: A Toy Model Analysis
por: Yang, Huitao
Publicado: (2025)

Advancing Deep Learning through Probability Engineering: A Pragmatic Paradigm for Modern AI
por: Zhang, Jianyi
Publicado: (2025)

Beyond Propagation of Chaos: A Stochastic Algorithm for Mean Field Optimization
por: Tankala, Chandan, et al.
Publicado: (2025)

Deep Conditional Measure Quantization
por: Turinici, Gabriel
Publicado: (2023)

$α$-TCAV: A Unified Framework for Testing with Concept Activation Vectors
por: Schnoor, Ekkehard, et al.
Publicado: (2026)

Representative Arm Identification: A fixed confidence approach to identify cluster representatives
por: Gharat, Sarvesh, et al.
Publicado: (2024)

Note on Martingale Theory and Applications
por: Zou, Xiandong
Publicado: (2026)

Soft-to-Hard Routing in Sparse Mixture-of-Experts Models
por: Rastegar, Reza
Publicado: (2026)

Generalisation of Total Uncertainty in AI: A Theoretical Study
por: Shariatmadar, Keivan
Publicado: (2024)

Generalized Gaussian Temporal Difference Error for Uncertainty-aware Reinforcement Learning
por: Kim, Seyeon, et al.
Publicado: (2024)

On the Equivalence of Random Network Distillation, Deep Ensembles, and Bayesian Inference
por: Zanger, Moritz A., et al.
Publicado: (2026)

Neural Hamiltonian Operator
por: Qi, Qian
Publicado: (2025)

Neural Thermodynamic Laws for Large Language Model Training
por: Liu, Ziming, et al.
Publicado: (2025)

DeepOHeat-v1: Efficient Operator Learning for Fast and Trustworthy Thermal Simulation and Optimization in 3D-IC Design
por: Yu, Xinling, et al.
Publicado: (2025)

A Neural Scaling Law from Lottery Ticket Ensembling
por: Liu, Ziming, et al.
Publicado: (2023)

Toward Dynamic Stability Assessment of Power Grid Topologies using Graph Neural Networks
por: Nauck, Christian, et al.
Publicado: (2022)

Bayesian Inference with Deep Weakly Nonlinear Networks
por: Hanin, Boris, et al.
Publicado: (2024)

Hybrid Probabilistic Forecasting of Under-Five Malaria Admissions in Ghana: A Gaussian Process Regression with Holt-Winters Smoothing
por: Ansah-Narh, T., et al.
Publicado: (2026)

Selective Reviews of Bandit Problems in AI via a Statistical View
por: Zhou, Pengjie, et al.
Publicado: (2024)

TowerDebias: A Novel Unfairness Removal Method Based on the Tower Property
por: Matloff, Norman, et al.
Publicado: (2024)

Combining Statistical Depth and Fermat Distance for Uncertainty Quantification
por: Nguyen, Hai-Vy, et al.
Publicado: (2024)

A Systematic Literature Review of Spatio-Temporal Graph Neural Network Models for Time Series Forecasting and Classification
por: Corradini, Flavio, et al.
Publicado: (2024)

How to Tame Your LLM: Semantic Collapse in Continuous Systems
por: Wyss, C. M.
Publicado: (2025)

Physics-Informed Inference Time Scaling for Solving High-Dimensional PDE via Defect Correction
por: Fan, Zexi, et al.
Publicado: (2025)

Efficient Risk-sensitive Planning via Entropic Risk Measures
por: Marthe, Alexandre, et al.
Publicado: (2025)

On Training-Test (Mis)alignment in Unsupervised Combinatorial Optimization: Observation, Empirical Exploration, and Analysis
por: Bu, Fanchen, et al.
Publicado: (2025)

Natural Latents: Latent Variables Stable Across Ontologies
por: Wentworth, John, et al.
Publicado: (2025)

Virtual Parameter Sharpening: Dynamic Low-Rank Perturbations for Inference-Time Reasoning Enhancement
por: Kublashvili, Saba
Publicado: (2025)