Towards a Law of Iterated Expectations for Heuristic Estimators
Safety Alignment Should Be Made More Than Just a Few Tokens Deep
Deep de Finetti: Recovering Topic Distributions from Large Language Models
How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?
Dynamical versus Bayesian Phase Transitions in a Toy Model of Superposition
Supervised Pretraining Can Learn In-Context Reinforcement Learning
Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression
Posterior sampling for multi-agent reinforcement learning: solving extensive games with imperfect information
Fundamental Limitations of Alignment in Large Language Models
Emergence of belief-like representations through reinforcement learning
Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities
Mortality postponement and compression at older ages in human cohorts
How do psychology researchers interpret the results of multiple replication studies?
Robust Bayesian meta-analysis: Addressing publication bias with model-averaging
Robust Bayesian meta-analysis: Model-averaging across complementary publication bias adjustment methods
AlphaZe∗∗: AlphaZero-like baselines for imperfect information games are surprisingly strong
What learning algorithm is in-context learning? Investigations with linear models
Laplace’s demon in biology: Models of evolutionary prediction
Are Most Published Criminological Research Findings Wrong? Taking Stock of Criminological Research using a Bayesian Simulation Approach
A Provably Efficient Model-Free Posterior Sampling Method for Episodic Reinforcement Learning
Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training
Greedy Bayesian Posterior Approximation with Deep Ensembles
RL with KL penalties is better viewed as Bayesian inference
Fast and Accurate Bayesian Polygenic Risk Modeling with Variational Inference
On-the-fly Strategy Adaptation for ad-hoc Agent Coordination
The InterModel Vigorish (IMV): A flexible and portable approach for quantifying predictive accuracy with binary outcomes
How to Learn and Represent Abstractions: An Investigation using Symbolic Alchemy
An Experimental Design Perspective on Model-Based Reinforcement Learning
Prior knowledge elicitation: The past, present, and future
Improving GWAS discovery and genomic prediction accuracy in Biobank data
An Explanation of In-context Learning as Implicit Bayesian Inference
Unifying individual differences in personality, predictability and plasticity: A practical guide
A confirmation bias in perceptual decision-making due to hierarchical approximate inference
MegaLMM: Mega-scale linear mixed models for genomic predictions with thousands of traits
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability
No Need to Choose: Robust Bayesian Meta-Analysis with Competing Publication Bias Adjustment Methods
Maternal Judgments of Child Numeracy and Reading Ability Predict Gains in Academic Achievement and Interest
Genetic sensitivity analysis: Adjusting for genetic confounding in epidemiological associations
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020
Maximal positive controls: A method for estimating the largest plausible effect size
Informational Herding, Optimal Experimentation, and Contrarianism
The statistical properties of RCTs and a proposal for shrinkage
Hot under the collar: A latent measure of interstate hostility
What matters more for entrepreneurship success? A meta-analysis comparing general mental ability and emotional intelligence in entrepreneurial settings
From Probability to Consilience: How Explanatory Values Implement Bayesian Reasoning
Searching for the Backfire Effect: Measurement and Design Considerations
Laplace’s Theories of Cognitive Illusions, Heuristics and Biases
Exploring Bayesian Optimization: Breaking Bayesian Optimization into small, sizeable chunks
Bayesian REX: Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences
Bayesian Deep Learning and a Probabilistic Perspective of Generalization
Why the Increasing Use of Complex Causal Models Is a Problem: On the Danger Sophisticated Theoretical Narratives Pose to Truth
Improved polygenic prediction by Bayesian multiple regression on summary statistics
The propensity for aggressive behavior and lifetime incarceration risk: A test for gene-environment interaction (G × E) using whole-genome data
Approximate Inference in Discrete Distributions with Monte Carlo Tree Search and Value Functions
Bayesian parameter estimation using conditional variational autoencoders for gravitational-wave astronomy
Estimating Distributional Models with brms: Additive Distributional Models
Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams
Is the FDA too conservative or too aggressive?: A Bayesian decision analysis of clinical trial design
Bayesian Statistics in Sociology: Past, Present, and Future
The Bayesian Superorganism III: externalized memories facilitate distributed sampling
The Bayesian Superorganism I: collective probability estimation
Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning
Computational mechanisms of curiosity and goal-directed exploration
Accurate Uncertainties for Deep Learning Using Calibrated Regression
The Alignment Problem for Bayesian History-Based Reinforcement Learners
Mining gold from implicit models to improve likelihood-free inference
Deep learning generalizes because the parameter-function map is biased towards simple functions
Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling
Implicit Causal Models for Genome-wide Association Studies
DropoutDAgger: A Bayesian Approach to Safe Imitation Learning
Better Decision Making in Drug Development Through Adoption of Formal Prior Elicitation
The prior can generally only be understood in the context of the likelihood
Statistical correction of the Winner’s Curse explains replication variability in quantitative trait genome-wide association studies
Structured Bayesian Pruning via Log-Normal Multiplicative Noise
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Human collective intelligence as distributed Bayesian inference
PHENIX: A multiple-phenotype imputation method for genetic studies
Probabilistic Integration: A Role in Statistical Computation?
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Optimal Regret Analysis of Thompson Sampling in Stochastic Multi-armed Bandit Problem with Multiple Plays
Gaussian Processes for Data-Efficient Learning in Robotics and Control
LDpred: Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores
Simultaneous Discovery, Estimation and Prediction Analysis of Complex Traits Using a Bayesian Mixture Model
Predictive distributions for between-study heterogeneity and simple methods for their application in Bayesian meta-analysis
One Hundred Years of Statistical Developments in Animal Breeding
Machine Teaching for Bayesian Learners in the Exponential Family
(More) Efficient Reinforcement Learning via Posterior Sampling
Understanding Predictive Information Criteria for Bayesian Models
(More) Efficient Reinforcement Learning via Posterior Sampling [PSRL]
Practical Bayesian Optimization of Machine Learning Algorithms
Learning is planning: near Bayes-optimal reinforcement learning via Monte-Carlo tree search
Learning Performance of Prediction Markets with Kelly Bettors
Bayesian Active Learning for Classification and Preference Learning
PILCO: A Model-Based and Data-Efficient Approach to Policy Search
Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments
Lack of Confidence in Approximate Bayesian Computation Model Choice
Are birds smarter than mathematicians? Pigeons (Columba livia) perform optimally on a version of the Monty Hall Dilemma
Observed Universality of Phase Transitions in High-Dimensional Geometry, with Implications for Modern Data Analysis and Signal Processing
When Superstars Flop: Public Status and Choking Under Pressure in International Soccer Penalty Shootouts
Models for potentially biased evidence in meta-analysis using empirically based priors
Verbal Probability Expressions In National Intelligence Estimates: A Comprehensive Analysis Of Trends From The Fifties Through Post-9/11
Introduction history of Drosophila subobscura in the New World: a microsatellite-based survey using ABC methods
Experiments on partisanship and public opinion: Party cues, false beliefs, and Bayesian updating
The Optimizer’s Curse: Skepticism and Postdecision Surprise in Decision Analysis
Three Statistical Paradoxes in the Interpretation of Group Differences: Illustrated with Medical School Admission and Licensing Data
Estimation of Non-Normalized Statistical Models by Score Matching
The Bayesian brain: the role of uncertainty in neural coding and computation
Two Statistical Paradoxes in the Interpretation of Group Differences: Illustrated with Medical School Admission and Licensing Data
Constructing a Logic of Plausible Inference: A Guide to Cox’s Theorem
Classical Multilevel and Bayesian Approaches to Population Size Estimation Using Multiple Lists
A Conversation With I. Richard Savage (with the Assistance of Bruce Spencer)
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
Statistical Issues in the Analysis of Data Gathered in the New Designs
Is There Sufficient Historical Evidence to Establish the Resurrection of Jesus?
The Relevance of Group Membership for Personnel Selection: A Demonstration Using Bayes’ Theorem
Perceptual-cognitive universals as reflections of the world
The Influence of Prior Beliefs on Scientific Judgments of Evidence Quality
Statistical Theory of Learning Curves under Entropic Loss Criterion
Information-Based Objective Functions for Active Data Selection
The 1988 Neyman Memorial Lecture: A Galtonian Perspective on Shrinkage Estimators
The Double Exponential Distribution: Using Calculus to Find a Maximum Likelihood Estimator
This Week’s Citation Classic: Nearest Neighbor Pattern Classification
To Understand Regression from Parent to Offspring, Think Statistically
Stein‘s Paradox in Statistics: The Best Guess about the Future Is Usually Obtained by Computing the Average of past Events. Stein’s Paradox Defines Circumstances in Which There Are Estimators Better Than the Arithmetic Average
Interpreting regression toward the mean in developmental research
Inference in an Authorship Problem: A Comparative Study of Discrimination Methods Applied to the Authorship of the Disputed Federalist Papers
Evaluating the Effect of Inadequately Measured Variables in Partial Correlation Analysis
Mr Keynes on Probability [Review of J. M. Keynes, A Treatise on Probability, 1921]
Philosophical Essay on Probabilities, Chapter 11: Concerning the Probabilities of Testimonies
Why Generalization in RL Is Difficult: Epistemic POMDPs and Implicit Partial Observability [Blog]
An Experimental Design Perspective on Model-Based Reinforcement Learning [Blog]
brms: an R package for Bayesian generalized multivariate non-linear multilevel models using Stan
Approximate Bayes Optimal Policy Search Using Neural Networks
Research Update: Towards a Law of Iterated Expectations for Heuristic Estimators
Why We Can’t Take Expected Value Estimates Literally (Even When They’re Unbiased)
Why Neural Networks Generalise, and Why They Are (Kind Of) Bayesian
Simple versus Short: Higher-Order Degeneracy and Error-Correction
From Classical Methods to Generative Models: Tackling the Unreliability of Neuroscientific Measures in Mental Health Research
Tiny Data, Approximate Bayesian Computation and the Socks of Karl Broman
Probable Points and Credible Intervals, Part 2: Decision Theory
2022-kadavath-figure4-anthropiclmscalingofanswercalibrationvsmodelsizefrom08bto52b.png
2019-12-09-gwern-goodreads-abandonment-bayesian-averageratingspline.png
2019-12-09-gwern-goodreads-abandonment-bayesian-yearspline.png
http://vision.psych.umn.edu/groups/schraterlab/dearden98bayesian.pdf
https://github.com/cranmer/active_sciencing/blob/master/README.md
https://joe-antognini.github.io/machine-learning/steins-paradox
https://joecarlsmith.com/2023/05/08/predictable-updating-about-ai-risk/
https://math.ucr.edu/home/baez/information/information_geometry_8.html
https://statmodeling.stat.columbia.edu/2023/04/18/chatgpt4-writes-stan-code-so-i-dont-have-to/
https://storage.googleapis.com/pub-tools-public-publication-data/pdf/f52ac33bc9d1adecd3a8037a7009b185fd934f0e.pdf
https://towardsdatascience.com/deep-neural-networks-are-biased-at-initialisation-towards-simple-functions-a63487edcb99
https://towardsdatascience.com/neural-networks-are-fundamentally-bayesian-bee9a172fad8
https://www.astralcodexten.com/p/against-learning-from-dramatic-events
https://www.berryconsultants.com/2023/09/14/if-bayesian-inference-doesnt-depend-on-the-experimental-design-then-why-does-bayesian-optimal-design-exist/
https://www.lesswrong.com/posts/GveDmwzxiYHSWtZbv/shannon-s-surprising-discovery-1
https://www.lesswrong.com/posts/S54HKhxQyttNLATKu/deconfusing-direct-vs-amortised-optimization
https://www.lesswrong.com/posts/ZwshvqiqCvXPsZEct/the-learning-theoretic-agenda-status-2023
https://www.probabilistic-numerics.org/assets/ProbabilisticNumerics.pdf#page=3
Supervised Pretraining Can Learn In-Context Reinforcement Learning
Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities
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Robust Bayesian meta-analysis: Addressing publication bias with model-averaging
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What learning algorithm is in-context learning? Investigations with linear models
https%253A%252F%252Farxiv.org%252Fabs%252F2211.15661%2523google.html
Are Most Published Criminological Research Findings Wrong? Taking Stock of Criminological Research using a Bayesian Simulation Approach
https%253A%252F%252Farxiv.org%252Fabs%252F2207.05221%2523anthropic.html
RL with KL penalties is better viewed as Bayesian inference
Unifying individual differences in personality, predictability and plasticity: A practical guide
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No Need to Choose: Robust Bayesian Meta-Analysis with Competing Publication Bias Adjustment Methods
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The statistical properties of RCTs and a proposal for shrinkage
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The Alignment Problem for Bayesian History-Based Reinforcement Learners
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Predictive distributions for between-study heterogeneity and simple methods for their application in Bayesian meta-analysis
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%252Fdoc%252Fstatistics%252Fbayes%252F2013-kruschke.pdf.html
%252Fdoc%252Fstatistics%252Fbayes%252F2010-stigler-2.pdf.html
%252Fdoc%252Freinforcement-learning%252Fmodel%252F2010-silver.pdf.html
Introduction history of Drosophila subobscura in the New World: a microsatellite-based survey using ABC methods
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Estimation of Non-Normalized Statistical Models by Score Matching
https%253A%252F%252Fwww.jmlr.org%252Fpapers%252Fvolume6%252Fhyvarinen05a%252Fhyvarinen05a.pdf.html
The Relevance of Group Membership for Personnel Selection: A Demonstration Using Bayes’ Theorem
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Perceptual-cognitive universals as reflections of the world
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This Week’s Citation Classic: Nearest Neighbor Pattern Classification
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https%253A%252F%252Fjournals.plos.org%252Fploscompbiol%252Farticle%253Fid%253D10.1371%252Fjournal.pcbi.1002803.html
Wikipedia Bibliography:
