Maarten V. de Hoop
8 papers · 2019–2025 · 3 venues · across top CS/AI venues
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Machine Learning
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Deep Learning
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Optimization & Theory
(4)
Core Methods
(3)
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(3)
Artificial Intelligence
(2)
Computer Vision
(1)
Mathematics & Optimization
(1)
Bayesian & Probabilistic Β· Artificial Intelligence
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Bayesian & Probabilistic Β· Machine Learning
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Core AI
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Domain-Specific
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Mathematics
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Models
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Keywords
neural network
(2)
neural operator
(2)
inverse problem
(2)
universal approximator
(2)
source separation
(1)
attention mechanism
(1)
in-context learning
(1)
image reconstruction
(1)
fourier analysis
(1)
posterior sampling
(1)
implicit neural representation
(1)
random projection
(1)
operator learning
(1)
score-based diffusion model
(1)
numerical solver
(1)
score-based diffusion
(1)
homotopy continuation
(1)
interpretable representation
(1)
multi-layer perceptron
(1)
semi-algebraic function
(1)
Papers
Semialgebraic Neural Networks: From roots to representations
ICLR 2025
Transformers are Universal In-context Learners
ICLR 2025
Can neural operators always be continuously discretized?
NeurIPS 2024
Implicit Neural Representations and the Algebra of Complex Wavelets
ICLR 2024
Conditional score-based diffusion models for Bayesian inference in infinite dimensions
NeurIPS 2023
Globally injective and bijective neural operators
NeurIPS 2023
Unearthing InSights into Mars: Unsupervised Source Separation with Limited Data
ICML 2023
Random mesh projectors for inverse problems
ICLR 2019