Cover Image

Even More Guarantees for Variational Inference in the Presence of Symmetries

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zellinger, Lena, Vergari, Antonio
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Computation
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Generalized Guarantees for Variational Inference in the Presence of Even and Elliptical Symmetry
by: Margossian, Charles C., et al.
Published: (2025)

Scalable Expectation Estimation with Subtractive Mixture Models
by: Zellinger, Lena, et al.
Published: (2025)

How to Approximate Inference with Subtractive Mixture Models
by: Zellinger, Lena, et al.
Published: (2026)

Symmetry Guarantees Statistic Recovery in Variational Inference
by: Marks, Daniel, et al.
Published: (2026)

Counterfactual Reasoning with Knowledge Graph Embeddings
by: Zellinger, Lena, et al.
Published: (2024)

Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box
by: Giordano, Ryan, et al.
Published: (2023)

Natural Language-Based Synthetic Data Generation for Cluster Analysis
by: Zellinger, Michael J., et al.
Published: (2023)

Binary Losses for Density Ratio Estimation
by: Zellinger, Werner
Published: (2024)

Towards Logically Consistent Language Models via Probabilistic Reasoning
by: Calanzone, Diego, et al.
Published: (2024)

Learning with Noisy Labels by Adaptive Gradient-Based Outlier Removal
by: Sedova, Anastasiia, et al.
Published: (2023)

Cascade Speculative Drafting for Even Faster LLM Inference
by: Chen, Ziyi, et al.
Published: (2023)

Variational Inference with Coverage Guarantees in Simulation-Based Inference
by: Patel, Yash, et al.
Published: (2023)

The Theory and Practice of MAP Inference over Non-Convex Constraints
by: Kurscheidt, Leander, et al.
Published: (2026)

Logically Consistent Language Models via Neuro-Symbolic Integration
by: Calanzone, Diego, et al.
Published: (2024)

Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians
by: Huix, Tom, et al.
Published: (2024)

Can VLMs Reason Robustly? A Neuro-Symbolic Investigation
by: Chen, Weixin, et al.
Published: (2026)

Sum of Squares Circuits
by: Loconte, Lorenzo, et al.
Published: (2024)

Variational Transdimensional Inference
by: Davies, Laurence, et al.
Published: (2025)

Provably Scalable Black-Box Variational Inference with Structured Variational Families
by: Ko, Joohwan, et al.
Published: (2024)

On Faster Marginalization with Squared Circuits via Orthonormalization
by: Loconte, Lorenzo, et al.
Published: (2024)

What can Large Language Models Capture about Code Functional Equivalence?
by: Maveli, Nickil, et al.
Published: (2024)

Practical Performance Guarantees for Pipelined DNN Inference
by: Archer, Aaron, et al.
Published: (2023)

Optimization Guarantees for Square-Root Natural-Gradient Variational Inference
by: Kumar, Navish, et al.
Published: (2025)

Pathwise Gradient Variance Reduction with Control Variates in Variational Inference
by: Ng, Kenyon, et al.
Published: (2024)

Variational Inference for Bayesian MIDAS Regression
by: Simeone, Luigi
Published: (2026)

Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs
by: Margossian, Charles C., et al.
Published: (2024)

Rotated Mean-Field Variational Inference and Iterative Gaussianization
by: Chen, Yifan, et al.
Published: (2025)

Taming the Sigmoid Bottleneck: Provably Argmaxable Sparse Multi-Label Classification
by: Grivas, Andreas, et al.
Published: (2023)

An Embarrassingly Simple Way to Optimize Orthogonal Matrices at Scale
by: Javaloy, Adrián, et al.
Published: (2026)

Rational Tuning of LLM Cascades via Probabilistic Modeling
by: Zellinger, Michael J., et al.
Published: (2025)

Efficiently Deploying LLMs with Controlled Risk
by: Zellinger, Michael J., et al.
Published: (2024)

Adaptive Inference-Time Compute: LLMs Can Predict if They Can Do Better, Even Mid-Generation
by: Manvi, Rohin, et al.
Published: (2024)

FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering
by: Qin, Juehang, et al.
Published: (2025)

Variational Inference Using Material Point Method
by: Huang, Yongchao
Published: (2024)

Theoretical Convergence Guarantees for Variational Autoencoders
by: Surendran, Sobihan, et al.
Published: (2024)

Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix
by: Margossian, Charles C., et al.
Published: (2024)

Linear Convergence of Black-Box Variational Inference: Should We Stick the Landing?
by: Kim, Kyurae, et al.
Published: (2023)

Anchored Variational Inference for Personalized Sequential Latent-State Models
by: Guo, Xingche
Published: (2026)

SIMSHIFT: A Benchmark for Adapting Neural Surrogates to Distribution Shifts
by: Setinek, Paul, et al.
Published: (2025)

Latent Thought Models with Variational Bayes Inference-Time Computation
by: Kong, Deqian, et al.
Published: (2025)