Stephen Bates
16 papers · 2020–2025 · 6 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (5) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (6) 🐝 Cross-Pollinator (4)
🏃
Academic Marathon
(5)
🧭
Keyword Pioneer
🐝
Cross-Pollinator
(4)
🔥
Unstoppable
(6)
💎
Century Club
(16)
⚡
Prolific Year
(5)
🗃️
Keyword Collector
(64)
Conferences
NIPS (6)
ICML (3)
AISTATS (2)
ICLR (2)
JMLR (2)
EMNLP (1)
Top co-authors
Keywords
uncertainty quantification
(5)
conformal prediction
(3)
quantile regression
(3)
information asymmetry
(2)
generative model
(2)
distribution shift
(1)
ensemble learning
(1)
algorithmic fairness
(1)
image super-resolution
(1)
distributed learning
(1)
hypothesis testing
(1)
label noise
(1)
domain generalization
(1)
fairness testing
(1)
electron microscopy
(1)
image regression
(1)
model averaging
(1)
medical imaging
(1)
inverse problem
(1)
representation learning
(1)
Papers
Thought calibration: Efficient and confident test-time scaling
EMNLP 2025
Contextual Online Decision Making with Infinite-Dimensional Functional Regression
ICML 2025
Label Noise Robustness of Conformal Prediction
JMLR 2024
Delegating Data Collection in Decentralized Machine Learning
AISTATS 2024
On Counterfactual Metrics for Social Welfare: Incentives, Ranking, and Information Asymmetry
AISTATS 2024
Conformal Risk Control
ICLR 2024
Online conformal prediction with decaying step sizes
ICML 2024
Class-Conditional Conformal Prediction with Many Classes
NIPS 2023
Calibrated Multiple-Output Quantile Regression with Representation Learning
JMLR 2023
Semantic uncertainty intervals for disentangled latent spaces
NIPS 2022
Robust Calibration with Multi-domain Temperature Scaling
NIPS 2022
Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging
ICML 2022
Improving Conditional Coverage via Orthogonal Quantile Regression
NIPS 2021
Test-time Collective Prediction
NIPS 2021
Uncertainty Sets for Image Classifiers using Conformal Prediction
ICLR 2021
Achieving Equalized Odds by Resampling Sensitive Attributes
NIPS 2020