Instance-Adaptive Parametrization for Amortized Variational Inference
Fuente:
arXiv
Saved in:
| Main Authors: | Pollastro, Andrea, Apicella, Andrea, Isgrò, Francesco, Prevete, Roberto |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Don't stop me now: Rethinking Validation Criteria for Model Parameter Selection
by: Apicella, Andrea, et al.
Published: (2026)
by: Apicella, Andrea, et al.
Published: (2026)
Toward the application of XAI methods in EEG-based systems
by: Apicella, Andrea, et al.
Published: (2022)
by: Apicella, Andrea, et al.
Published: (2022)
IMPACTX: improving model performance by appropriately constraining the training with teacher explanations
by: Apicella, Andrea, et al.
Published: (2025)
by: Apicella, Andrea, et al.
Published: (2025)
Don't Push the Button! Exploring Data Leakage Risks in Machine Learning and Transfer Learning
by: Apicella, Andrea, et al.
Published: (2024)
by: Apicella, Andrea, et al.
Published: (2024)
SincVAE: A new semi-supervised approach to improve anomaly detection on EEG data using SincNet and variational autoencoder
by: Pollastro, Andrea, et al.
Published: (2024)
by: Pollastro, Andrea, et al.
Published: (2024)
Towards a general framework for improving the performance of classifiers using XAI methods
by: Apicella, Andrea, et al.
Published: (2024)
by: Apicella, Andrea, et al.
Published: (2024)
JADAI: Jointly Amortizing Adaptive Design and Bayesian Inference
by: Bracher, Niels, et al.
Published: (2025)
by: Bracher, Niels, et al.
Published: (2025)
Fast and Robust Likelihood-Guided Diffusion Posterior Sampling with Amortized Variational Inference
by: Zheng, Léon, et al.
Published: (2026)
by: Zheng, Léon, et al.
Published: (2026)
Aligning Few-Step Generative Models by Amortizing Sample-based Variational Inference
by: Lee, Jaewoo, et al.
Published: (2026)
by: Lee, Jaewoo, et al.
Published: (2026)
MAVRL: Learning Reward Functions from Multiple Feedback Types with Amortized Variational Inference
by: Baur, Raphaël, et al.
Published: (2026)
by: Baur, Raphaël, et al.
Published: (2026)
It Just Takes Two: Scaling Amortized Inference to Large Sets
by: Wehenkel, Antoine, et al.
Published: (2026)
by: Wehenkel, Antoine, et al.
Published: (2026)
Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference
by: Schmitt, Marvin, et al.
Published: (2023)
by: Schmitt, Marvin, et al.
Published: (2023)
Iterative Amortized Inference: Unifying In-Context Learning and Learned Optimizers
by: Mittal, Sarthak, et al.
Published: (2025)
by: Mittal, Sarthak, et al.
Published: (2025)
ACTIVA: Amortized Causal Effect Estimation via Transformer-based Variational Autoencoder
by: Sauter, Andreas, et al.
Published: (2025)
by: Sauter, Andreas, et al.
Published: (2025)
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended Investigation
by: Schmitt, Marvin, et al.
Published: (2024)
by: Schmitt, Marvin, et al.
Published: (2024)
Enhancing Unimodal Latent Representations in Multimodal VAEs through Iterative Amortized Inference
by: Oshima, Yuta, et al.
Published: (2024)
by: Oshima, Yuta, et al.
Published: (2024)
Iterative Amortized Hierarchical VAE
by: Penninga, Simon W., et al.
Published: (2026)
by: Penninga, Simon W., et al.
Published: (2026)
In-Context Parametric Inference: Point or Distribution Estimators?
by: Mittal, Sarthak, et al.
Published: (2025)
by: Mittal, Sarthak, et al.
Published: (2025)
Amortized In-Context Bayesian Posterior Estimation
by: Mittal, Sarthak, et al.
Published: (2025)
by: Mittal, Sarthak, et al.
Published: (2025)
Amortized Sampling with Transferable Normalizing Flows
by: Tan, Charlie B., et al.
Published: (2025)
by: Tan, Charlie B., et al.
Published: (2025)
Amortized Optimal Transport from Sliced Potentials
by: Truong, Minh-Phuc, et al.
Published: (2026)
by: Truong, Minh-Phuc, et al.
Published: (2026)
Toward cross-subject and cross-session generalization in EEG-based emotion recognition: Systematic review, taxonomy, and methods
by: Apicella, Andrea, et al.
Published: (2022)
by: Apicella, Andrea, et al.
Published: (2022)
Amortized Active Causal Induction with Deep Reinforcement Learning
by: Annadani, Yashas, et al.
Published: (2024)
by: Annadani, Yashas, et al.
Published: (2024)
Adaptive Variational Inference in Probabilistic Graphical Models: Beyond Bethe, Tree-Reweighted, and Convex Free Energies
by: Leisenberger, Harald, et al.
Published: (2025)
by: Leisenberger, Harald, et al.
Published: (2025)
HyperTransport: Amortized Conditioning of T2I Generative Models
by: Maiorca, Valentino, et al.
Published: (2026)
by: Maiorca, Valentino, et al.
Published: (2026)
PIG: Physics-Informed Gaussians as Adaptive Parametric Mesh Representations
by: Kang, Namgyu, et al.
Published: (2024)
by: Kang, Namgyu, et al.
Published: (2024)
OpInf-LLM: Parametric PDE Solving with LLMs via Operator Inference
by: Wang, Zhuoyuan, et al.
Published: (2026)
by: Wang, Zhuoyuan, et al.
Published: (2026)
Amortized Linear-time Exact Shapley Value for Product-Kernel Methods
by: Mohammadi, Majid, et al.
Published: (2025)
by: Mohammadi, Majid, et al.
Published: (2025)
Amortized Latent Steering: Low-Cost Alternative to Test-Time Optimization
by: Egbuna, Nathan, et al.
Published: (2025)
by: Egbuna, Nathan, et al.
Published: (2025)
Amortized Planning with Large-Scale Transformers: A Case Study on Chess
by: Ruoss, Anian, et al.
Published: (2024)
by: Ruoss, Anian, et al.
Published: (2024)
Variational Inference via Smoothed Particle Hydrodynamics
by: Huang, Yongchao
Published: (2024)
by: Huang, Yongchao
Published: (2024)
Variational Autoencoders for Efficient Simulation-Based Inference
by: Nautiyal, Mayank, et al.
Published: (2024)
by: Nautiyal, Mayank, et al.
Published: (2024)
Amortized Reasoning Tree Search: Decoupling Proposal and Decision in Large Language Models
by: Hong, Zesheng, et al.
Published: (2026)
by: Hong, Zesheng, et al.
Published: (2026)
Deep Active Inference Agents for Delayed and Long-Horizon Environments
by: Yeganeh, Yavar Taheri, et al.
Published: (2025)
by: Yeganeh, Yavar Taheri, et al.
Published: (2025)
GEPS: Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning
by: Koupaï, Armand Kassaï, et al.
Published: (2024)
by: Koupaï, Armand Kassaï, et al.
Published: (2024)
Multi-Agent LLMs for Adaptive Acquisition in Bayesian Optimization
by: Carbonati, Andrea, et al.
Published: (2026)
by: Carbonati, Andrea, et al.
Published: (2026)
Bayesian Program Learning by Decompiling Amortized Knowledge
by: Palmarini, Alessandro B., et al.
Published: (2023)
by: Palmarini, Alessandro B., et al.
Published: (2023)
Active Inference Meeting Energy-Efficient Control of Parallel and Identical Machines
by: Yeganeh, Yavar Taheri, et al.
Published: (2024)
by: Yeganeh, Yavar Taheri, et al.
Published: (2024)
Amortized Variational Inference for Joint Posterior and Predictive Distributions in Bayesian Uncertainty Quantification
by: Feng, Nan, et al.
Published: (2026)
by: Feng, Nan, et al.
Published: (2026)
Variational Learning Induces Adaptive Label Smoothing
by: Yang, Sin-Han, et al.
Published: (2025)
by: Yang, Sin-Han, et al.
Published: (2025)
Similar Items
-
Don't stop me now: Rethinking Validation Criteria for Model Parameter Selection
by: Apicella, Andrea, et al.
Published: (2026) -
Toward the application of XAI methods in EEG-based systems
by: Apicella, Andrea, et al.
Published: (2022) -
IMPACTX: improving model performance by appropriately constraining the training with teacher explanations
by: Apicella, Andrea, et al.
Published: (2025) -
Don't Push the Button! Exploring Data Leakage Risks in Machine Learning and Transfer Learning
by: Apicella, Andrea, et al.
Published: (2024) -
SincVAE: A new semi-supervised approach to improve anomaly detection on EEG data using SincNet and variational autoencoder
by: Pollastro, Andrea, et al.
Published: (2024)