17 citations · 26 across the 18 of their papers we have counts for
7 papers · 1 filter
Langevin-Informed Transfer Learning: Replacing Target Samples by Black-Box Feedback
Vladimir R. Kostic, Karim Lounici, Hélène Halconruy +3
Many scientific and machine learning systems, from molecular dynamics to diffusion models and beyond, are governed by stochastic dynamics with low-dimensional structure, evolving o…
Learning Conditional Expectation Operators via Functional Newton Updates
Thiago Ramos, Alek Fröhlich, Daniel Perazzo +1
We introduce the Functional Spectral-Newton Method (FSNM) for learning the leading singular structure of a conditional expectation operator without fixing a basis or reproducing ke…
Reward-free Pretraining for Reinforcement Learning via Occupancy Coverage Maximization
Marco Pratticò, Pietro Novelli, Massimiliano Pontil +1
Sparse rewards pose a central challenge in reinforcement learning, since agents receive no informative signal until they reach their goal. Intrinsic-reward methods address this iss…
Morphologically Equivariant Flow Matching for Bimanual Mobile Manipulation
Max Siebenborn, Daniel Ordoñez Apraez, Sophie Lueth +4
Mobile manipulation requires coordinated control of high-dimensional, bimanual robots. Imitation learning methods have been broadly used to solve these robotic tasks, yet typically…
Toeplitz Based Spectral Methods for Data-driven Dynamical Systems
Vladimir R. Kostic, Karim Lounici, Massimiliano Pontil
We introduce a Toeplitz-based framework for data-driven spectral estimation of linear evolution operators in dynamical systems. Focusing on transfer and Koopman operators from equi…
kooplearn: A Scikit-Learn Compatible Library of Algorithms for Evolution Operator Learning
Giacomo Turri, Grégoire Pacreau, Giacomo Meanti +8
kooplearn is a machine-learning library that implements linear, kernel, and deep-learning estimators of dynamical operators and their spectral decompositions. kooplearn can model b…
SpectraFormer: an Attention-Based Raman Unmixing Tool for Accessing the Graphene Buffer-Layer Signature on SiC
Dmitriy Poteryayev, Pietro Novelli, Annalisa Coriolano +7
Raman spectroscopy is a key tool for graphene characterization, yet its application to graphene grown on silicon carbide (SiC) is strongly limited by the intense and variable secon…