Sebastian Farquhar
14 papers · 2020–2025 · 5 venues · across top CS/AI venues
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Research topics
Machine Learning
(12)
Artificial Intelligence
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Optimization & Theory
(9)
Core AI
(6)
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(6)
Deep Learning
(3)
Application Areas
(3)
Bayesian & Probabilistic
(3)
Models
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Knowledge & Reasoning
(2)
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Reasoning
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Healthcare & Medicine
(1)
Mathematics & Optimization
(1)
Natural Language Processing
(1)
Keywords
variational inference
(3)
active learning
(3)
bayesian neural network
(3)
causal inference
(2)
posterior approximation
(2)
model evaluation
(2)
acquisition strategy
(2)
acquisition function
(2)
large language model
(2)
sample efficiency
(2)
model architecture
(1)
question answering
(1)
game theory
(1)
policy learning
(1)
medical imaging
(1)
uncertainty sampling
(1)
curriculum learning
(1)
mean-field approximation
(1)
ai safety
(1)
hyperparameter optimization
(1)
Papers
MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking
ICML 2025
Discovering Agents (Abstract Reprint)
AAAI 2024
Do Bayesian Neural Networks Need To Be Fully Stochastic?
AISTATS 2023
Prediction-Oriented Bayesian Active Learning
AISTATS 2023
Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation
ICLR 2023
Tracr: Compiled Transformers as a Laboratory for Interpretability
NeurIPS 2023
Active Surrogate Estimators: An Active Learning Approach to Label-Efficient Model Evaluation
NeurIPS 2022
Path-Specific Objectives for Safer Agent Incentives
AAAI 2022
Prioritized Training on Points that are Learnable, Worth Learning, and not yet Learnt
ICML 2022
Prospect Pruning: Finding Trainable Weights at Initialization using Meta-Gradients
ICLR 2022
Active Testing: Sample-Efficient Model Evaluation
ICML 2021
On Statistical Bias In Active Learning: How and When to Fix It
ICLR 2021
Liberty or Depth: Deep Bayesian Neural Nets Do Not Need Complex Weight Posterior Approximations
NeurIPS 2020
Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
AISTATS 2020