Noah Hollmann
7 papers · 2022–2025 · 3 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
Jump to papers ↓
🌍
Conference Polyglot · Bronze
🌉
Interdisciplinary Bridge · Bronze
🗺️
Taxonomy Completionist
(18)
👑
Triple Crown
Venues
Top co-authors
Research topics
Machine Learning
(7)
Artificial Intelligence
(6)
Optimization & Theory
(5)
Core Methods
(4)
Deep Learning
(3)
Bayesian & Probabilistic
(2)
Core AI
(2)
Learning Paradigms
(2)
Knowledge & Reasoning
(1)
Mathematics & Optimization
(1)
Application Areas
(1)
Architectures
(1)
Learning Types
(1)
Models
(1)
Optimization
(1)
Keywords
prior-data fitted network
(3)
bayesian inference
(3)
in-context learning
(2)
gaussian process
(2)
tabular data
(2)
bayesian model
(1)
distribution shift
(1)
prior distribution
(1)
bayesian optimization
(1)
posterior approximation
(1)
amortized inference
(1)
surrogate model
(1)
synthetic data
(1)
foundation model
(1)
structural causal model
(1)
feature engineering
(1)
tabular classification
(1)
automated machine learning
(1)
posterior predictive distribution
(1)
surrogate modeling
(1)
Papers
FairPFN: A Tabular Foundation Model for Causal Fairness
ICML 2025
Position: The Future of Bayesian Prediction Is Prior-Fitted
ICML 2025
Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data
NeurIPS 2024
Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering
NeurIPS 2023
PFNs4BO: In-Context Learning for Bayesian Optimization
ICML 2023
TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second
ICLR 2023
Transformers Can Do Bayesian Inference
ICLR 2022