Pietro Michiardi
16 papers · 2017–2025 · 5 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (30) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
π€
Dynamic Duo
(11)
π
Grand Slam
π§¬
Topic Evolution
π
Century Club Β· Bronze
ποΈ
Keyword Collector
(79)
π₯
Unstoppable Β· Bronze
Top co-authors
Research topics
Machine Learning
(14)
Optimization & Theory
(10)
Deep Learning
(9)
Artificial Intelligence
(8)
Models
(8)
Bayesian & Probabilistic Β· Artificial Intelligence
(5)
Core Methods
(4)
Learning Types
(4)
Bayesian & Probabilistic Β· Machine Learning
(3)
Architectures
(2)
Core AI Β· Artificial Intelligence
(2)
Techniques
(2)
Computer Vision
(1)
Mathematics & Optimization
(1)
Core AI Β· Computer Vision
(1)
Keywords
variational inference
(4)
uncertainty quantification
(3)
gaussian process
(3)
variational autoencoder
(3)
mutual information
(2)
generative model
(2)
diffusion model
(2)
model selection
(1)
image generation
(1)
image classification
(1)
model calibration
(1)
kl divergence
(1)
rule-based learning
(1)
image translation
(1)
bayesian inference
(1)
multi-task learning
(1)
ensemble learning
(1)
sliced wasserstein distance
(1)
sparse approximation
(1)
deep learning
(1)
Papers
Information Theoretic Text-to-Image Alignment
ICLR 2025
Learning to Match Unpaired Data with Minimum Entropy Coupling
ICML 2025
MINDE: Mutual Information Neural Diffusion Estimation
ICLR 2024
S$Ξ©$I: Score-based O-INFORMATION Estimation
ICML 2024
Continuous-Time Functional Diffusion Processes
NeurIPS 2023
One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models
NeurIPS 2023
Revisiting the Effects of Stochasticity for Hamiltonian Samplers
ICML 2022
An Identifiable Double VAE For Disentangled Representations
ICML 2021
Maximum Roaming Multi-Task Learning
AAAI 2021
Model Selection for Bayesian Autoencoders
NeurIPS 2021
Sparse within Sparse Gaussian Processes using Neighbor Information
ICML 2021
LIBRE: Learning Interpretable Boolean Rule Ensembles
AISTATS 2020
Calibrating Deep Convolutional Gaussian Processes
AISTATS 2019
Good Initializations of Variational Bayes for Deep Models
ICML 2019
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification
NeurIPS 2018
Random Feature Expansions for Deep Gaussian Processes
ICML 2017