Pietro Novelli
10 papers · 2022–2025 · 4 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🗺️ Taxonomy Completionist (24) 🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🏆 Keyword Champion (3) 👑 Triple Crown
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Keyword Collector
(51)
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Prolific Year · Productive
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Century Club · Bronze
Venues
Top co-authors
Research topics
Machine Learning
(8)
Core Methods
(7)
Artificial Intelligence
(5)
Optimization & Theory
(5)
Mathematics & Optimization
(3)
Learning Paradigms
(3)
Deep Learning
(2)
Reinforcement Learning
(2)
Learning Types
(2)
Mathematics
(2)
Optimization
(2)
Data Science & Analytics
(1)
Applications
(1)
Architectures
(1)
Bayesian & Probabilistic
(1)
Keywords
koopman operator
(5)
spectral decomposition
(3)
dynamical system
(3)
reduced-rank regression
(2)
transfer operator
(2)
stochastic dynamical system
(2)
markov chain
(1)
reproducing kernel hilbert space
(1)
transfer learning
(1)
action-value function
(1)
kernel mean embedding
(1)
state representation learning
(1)
conditional distribution
(1)
operator theory
(1)
uniform bound
(1)
uncertainty quantification
(1)
feature map
(1)
spectral analysis
(1)
policy mirror descent
(1)
random projection
(1)
Papers
Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups
ICML 2025
Consistent Long-Term Forecasting of Ergodic Dynamical Systems
ICML 2024
Dynamics harmonic analysis of robotic systems: Application in data-driven Koopman modelling
L4DC 2024
Learning invariant representations of time-homogeneous stochastic dynamical systems
ICLR 2024
Neural Conditional Probability for Uncertainty Quantification
NeurIPS 2024
Operator World Models for Reinforcement Learning
NeurIPS 2024
Estimating Koopman operators with sketching to provably learn large scale dynamical systems
NeurIPS 2023
Sharp Spectral Rates for Koopman Operator Learning
NeurIPS 2023
Transfer learning for atomistic simulations using GNNs and kernel mean embeddings
NeurIPS 2023
Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces
NeurIPS 2022