David Holzmüller
8 papers · 2021–2025 · 4 venues · across top CS/AI venues
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Achievements
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🌍
Conference Polyglot · Bronze
🗺️
Taxonomy Completionist
(17)
🔥
Unstoppable · Bronze
Venues
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Research topics
Keywords
neural tangent kernel
(2)
tabular data
(2)
neural network
(2)
convergence analysis
(1)
deep learning theory
(1)
transformer
(1)
pretraining
(1)
gaussian process
(1)
gradient descent
(1)
gradient boosting
(1)
generalization error
(1)
uncertainty sampling
(1)
gibbs distribution
(1)
hyperparameter tuning
(1)
batch active learning
(1)
feature map
(1)
partial differential equation
(1)
relu activation
(1)
surrogate model
(1)
benign overfitting
(1)
Papers
Active Learning for Neural PDE Solvers
ICLR 2025
Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation
JMLR 2025
TabICL: A Tabular Foundation Model for In-Context Learning on Large Data
ICML 2025
Better by default: Strong pre-tuned MLPs and boosted trees on tabular data
NeurIPS 2024
A Framework and Benchmark for Deep Batch Active Learning for Regression
JMLR 2023
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension
NeurIPS 2023
Training Two-Layer ReLU Networks with Gradient Descent is Inconsistent
JMLR 2022
On the Universality of the Double Descent Peak in Ridgeless Regression
ICLR 2021