Tom Griffiths

Q: What Schools Are Affiliated With Tom Griffiths

Tom Griffiths is affiliated with the following schools: University of Western Australia, Brown University, University of California, Berkeley, Princeton University, Stanford University

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Tom Griffiths

Psychology

#1262

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#1551

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Cognitive Science

#46

World Rank

#47

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Cognitive Psychology

#93

World Rank

#96

Historical Rank

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Psychology

Tom Griffiths 's Degrees

PhD Cognitive Science University of California, Berkeley
Bachelors Psychology University of California, Berkeley

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Why Is Tom Griffiths Influential?

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According to Wikipedia, Thomas L. Griffiths is an Australian academic who is the Henry R. Luce Professor of Information Technology, Consciousness, and Culture at Princeton University. He studies human decision-making and its connection to problem-solving methods in computation. His book with Brian Christian, Algorithms to Live By: The Computer Science of Human Decisions, was named one of the "Best Books of 2016" by MIT Technology Review.

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Tom Griffiths 's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Finding scientific topics (2004) (5961)
The Author-Topic Model for Authors and Documents (2004) (1660)
How to Grow a Mind: Statistics, Structure, and Abstraction (2011) (1446)
Hierarchical Topic Models and the Nested Chinese Restaurant Process (2003) (1120)
Topics in semantic representation. (2007) (1072)
Natural speech reveals the semantic maps that tile human cerebral cortex (2016) (985)
Infinite latent feature models and the Indian buffet process (2005) (830)
Theory-based Bayesian models of inductive learning and reasoning (2006) (772)
Learning Systems of Concepts with an Infinite Relational Model (2006) (747)
Generalization, similarity, and Bayesian inference. (2001) (708)
Probabilistic Topic Models (2007) (691)
The nested chinese restaurant process and bayesian nonparametric inference of topic hierarchies (2007) (667)
Probabilistic author-topic models for information discovery (2004) (666)
Integrating Topics and Syntax (2004) (615)
Structure and strength in causal induction (2005) (595)
Bayesian models of cognition (2008) (548)
Toward a Rational and Mechanistic Account of Mental Effort. (2017) (547)
Optimal Predictions in Everyday Cognition (2006) (508)
Probabilistic models of cognition: exploring representations and inductive biases (2010) (475)
A Bayesian framework for word segmentation: Exploring the effects of context (2009) (453)
The 2005 PASCAL Visual Object Classes Challenge (2005) (443)
Nonparametric Latent Feature Models for Link Prediction (2009) (420)
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes (2018) (419)
The Indian Buffet Process: An Introduction and Review (2011) (419)
Innateness and culture in the evolution of language (2006) (381)
A fully Bayesian approach to unsupervised part-of-speech tagging (2007) (366)
One and Done? Optimal Decisions From Very Few Samples (2014) (347)
Contextual Dependencies in Unsupervised Word Segmentation (2006) (341)
A Rational Analysis of Rule-Based Concept Learning (2008) (339)
Rational approximations to rational models: alternative algorithms for category learning. (2010) (339)
Theory-based causal induction. (2009) (335)
Learning author-topic models from text corpora (2010) (331)
Adaptor Grammars: A Framework for Specifying Compositional Nonparametric Bayesian Models (2006) (303)
Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the Algorithmic (2015) (295)
Language Evolution by Iterated Learning With Bayesian Agents (2007) (265)
Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources (2019) (259)
Online Inference of Topics with Latent Dirichlet Allocation (2009) (244)
The influence of categories on perception: explaining the perceptual magnet effect as optimal statistical inference. (2009) (231)
A tutorial introduction to Bayesian models of cognitive development (2011) (228)
Bayesian Inference for PCFGs via Markov Chain Monte Carlo (2007) (225)
Interpolating between types and tokens by estimating power-law generators (2005) (224)
A rational account of pedagogical reasoning: Teaching by, and learning from, examples (2014) (219)
Iterated learning: Intergenerational knowledge transmission reveals inductive biases (2007) (206)
Children’s imitation of causal action sequences is influenced by statistical and pedagogical evidence (2011) (203)
The Hierarchical Cortical Organization of Human Speech Processing (2017) (176)
Unsupervised Topic Modelling for Multi-Party Spoken Discourse (2006) (175)
Changes in cognitive flexibility and hypothesis search across human life history from childhood to adolescence to adulthood (2017) (175)
Reconciling intuitive physics and Newtonian mechanics for colliding objects. (2013) (174)
A role for the developing lexicon in phonetic category acquisition. (2013) (173)
Can being scared cause tummy aches? Naive theories, ambiguous evidence, and preschoolers' causal inferences. (2007) (168)
When children are better (or at least more open-minded) learners than adults: Developmental differences in learning the forms of causal relationships (2014) (168)
The evolution of frequency distributions: Relating regularization to inductive biases through iterated learning (2009) (168)
Modeling human performance in statistical word segmentation (2010) (158)
Human Uncertainty Makes Classification More Robust (2019) (154)
Structure Learning in Human Causal Induction (2000) (153)
On the Utility of Learning about Humans for Human-AI Coordination (2019) (150)
Bridging Levels of Analysis for Probabilistic Models of Cognition (2012) (148)
A more rational model of categorization (2006) (143)
How the Bayesians got their beliefs (and what those beliefs actually are): comment on Bowers and Davis (2012). (2012) (139)
Exemplar models as a mechanism for performing Bayesian inference (2010) (138)
Advances in Neural Information Processing Systems 21 (1993) (133)
Prediction and Semantic Association (2002) (132)
When Younger Learners Can Be Better (or at Least More Open-Minded) Than Older Ones (2015) (131)
Bayesian nonparametric latent feature models (2007) (129)
Investigating Human Priors for Playing Video Games (2018) (126)
Random walks on semantic networks can resemble optimal foraging. (2015) (125)
The anchoring bias reflects rational use of cognitive resources (2018) (125)
Automated reconstruction of ancient languages using probabilistic models of sound change (2013) (121)
From mere coincidences to meaningful discoveries (2007) (120)
Win-Stay, Lose-Sample: A simple sequential algorithm for approximating Bayesian inference (2014) (118)
Google and the Mind (2007) (118)
Strategy Selection as Rational Metareasoning (2017) (112)
A probabilistic approach to semantic representation (2019) (112)
Words as alleles: connecting language evolution with Bayesian learners to models of genetic drift (2010) (110)
Discovering Latent Classes in Relational Data (2004) (110)
Rational variability in children’s causal inferences: The Sampling Hypothesis (2013) (106)
Modeling the effects of memory on human online sentence processing with particle filters (2008) (106)
Theoretical and empirical evidence for the impact of inductive biases on cultural evolution (2008) (103)
Probabilistic inference in human semantic memory (2006) (102)
Formalizing Neurath’s Ship: Approximate Algorithms for Online Causal Learning (2016) (99)
A Non-Parametric Bayesian Method for Inferring Hidden Causes (2006) (99)
Learning phonetic categories by learning a lexicon (2009) (98)
Intuitive theories as grammars for causal inference (2007) (98)
Theory-Based Causal Inference (2002) (96)
Overrepresentation of Extreme Events in Decision Making Reflects Rational Use of Cognitive Resources (2017) (95)
Faster Teaching by POMDP Planning (2011) (95)
"Burn-in, bias, and the rationality of anchoring" (2012) (92)
Parametric Embedding for Class Visualization (2004) (91)
Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations (2017) (90)
A probabilistic model of theory formation (2010) (89)
Bayes and Blickets: Effects of Knowledge on Causal Induction in Children and Adults (2011) (89)
Individuals with cerebellar degeneration show similar adaptation deficits with large and small visuomotor errors. (2013) (88)
The Rational Basis of Representativeness (2001) (88)
Learning the Form of Causal Relationships Using Hierarchical Bayesian Models (2009) (87)
Word-level information influences phonetic learning in adults and infants (2013) (86)
A Bayesian View of Language Evolution by Iterated Learning - eScholarship (2005) (85)
Producing Power-Law Distributions and Damping Word Frequencies with Two-Stage Language Models (2011) (84)
Reconciling meta-learning and continual learning with online mixtures of tasks (2018) (84)
Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling (2009) (83)
The Sapir-Whorf Hypothesis and Probabilistic Inference: Evidence from the Domain of Color (2016) (81)
Integrating explanation and prediction in computational social science (2021) (81)
Structured Priors for Structure Learning (2006) (81)
Probabilistic models, learning algorithms, and response variability: sampling in cognitive development (2014) (80)
A rational model of function learning (2015) (80)
Rational metareasoning and the plasticity of cognitive control (2018) (79)
Manifesto for a new (computational) cognitive revolution (2015) (76)
Adapting Deep Network Features to Capture Psychological Representations (2016) (76)
Using Category Structures to Test Iterated Learning as a Method for Identifying Inductive Biases (2008) (74)
Uncovering mental representations with Markov chain Monte Carlo (2010) (74)
Algorithms to Live By: The Computer Science of Human Decisions (2016) (74)
Semi-Supervised Learning with Trees (2003) (73)
The Wisdom of Individuals: Exploring People's Knowledge About Everyday Events Using Iterated Learning (2009) (73)
Faster Teaching via POMDP Planning (2016) (72)
Inferring mass in complex scenes by mental simulation (2016) (71)
Dynamical Causal Learning (2002) (69)
The Child as Econometrician: A Rational Model of Preference Understanding in Children (2014) (69)
Modeling human function learning with Gaussian processes (2008) (68)
Are Convolutional Neural Networks or Transformers more like human vision? (2021) (68)
Two proposals for causal grammars (2007) (63)
Sources of developmental change in the efficiency of information search. (2016) (60)
Automatically Composing Representation Transformations as a Means for Generalization (2018) (60)
Doing more with less: meta-reasoning and meta-learning in humans and machines (2019) (60)
Cultural transmission results in convergence towards colour term universals (2013) (57)
Categorization as nonparametric Bayesian density estimation (2008) (57)
Evaluating Vector-Space Models of Word Representation, or, The Unreasonable Effectiveness of Counting Words Near Other Words (2017) (57)
A Probabilistic Approach to Diachronic Phonology (2007) (56)
The Phylogenetic Indian Buffet Process: A Non-Exchangeable Nonparametric Prior for Latent Features (2008) (55)
Latent Features in Similarity Judgments: A Nonparametric Bayesian Approach (2008) (54)
Predicting the future as Bayesian inference: people combine prior knowledge with observations when estimating duration and extent. (2011) (53)
Markov Chain Monte Carlo with People (2007) (52)
Particle Filtering for Nonparametric Bayesian Matrix Factorization (2006) (51)
Cognitive Model Priors for Predicting Human Decisions (2019) (51)
Pragmatic-Pedagogic Value Alignment (2017) (51)
Human memory search as a random walk in a semantic network (2012) (51)
Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies (2013) (51)
Using large-scale experiments and machine learning to discover theories of human decision-making (2021) (49)
Fixation patterns in simple choice reflect optimal information sampling (2019) (49)
Randomness and Coincidences: Reconciling Intuition and Probability Theory (2001) (48)
A rational analysis of the effects of memory biases on serial reproduction (2010) (48)
Infant directed speech is consistent with teaching (2016) (48)
Capturing human categorization of natural images by combining deep networks and cognitive models (2020) (46)
Finding the traces of behavioral and cognitive processes in big data and naturally occurring datasets (2017) (45)
Algorithm selection by rational metareasoning as a model of human strategy selection (2014) (45)
A rational model of preference learning and choice prediction by children (2008) (44)
Iterated learning and the cultural ratchet (2009) (44)
Seeking Confirmation Is Rational for Deterministic Hypotheses (2011) (44)
A nonparametric Bayesian framework for constructing flexible feature representations. (2013) (44)
Goal Inference Improves Objective and Perceived Performance in Human-Robot Collaboration (2016) (43)
Evaluating vector-space models of analogy (2017) (43)
Focal colors across languages are representative members of color categories (2016) (42)
Reconciling novelty and complexity through a rational analysis of curiosity. (2019) (42)
ITERATED LEARNING OF MULTIPLE LANGUAGES FROM MULTIPLE TEACHERS (2010) (41)
Probability, algorithmic complexity, and subjective randomness (2003) (40)
A Primer on Probabilistic Inference (2008) (40)
Modeling Transfer Learning in Human Categorization with the Hierarchical Dirichlet Process (2010) (40)
Think again? The amount of mental simulation tracks uncertainty in the outcome (2015) (38)
Evaluating Theory of Mind in Question Answering (2018) (38)
Introduction. Cultural transmission and the evolution of human behaviour (2008) (37)
Performing Bayesian Inference with Exemplar Models (2008) (37)
Rational analysis as a link between human memory and information retrieval (2008) (37)
Using Physical Theories to Infer Hidden Causal Structure (2004) (36)
NAÏVE THEORIES, AMBIGUOUS EVIDENCE Page 1 Running head: NAÏVE THEORIES AND AMBIGUOUS EVIDENCE Can being scared make your tummy ache? Naive theories, ambiguous evidence and preschoolers’ causal inferences (2007) (36)
Inferring action structure and causal relationships in continuous sequences of human action (2015) (35)
The imaginary fundamentalists: The unshocking truth about Bayesian cognitive science (2011) (35)
Children's causal inferences from conflicting testimony and observations. (2016) (34)
Tracing the roots of syntax with Bayesian phylogenetics (2014) (34)
Exploring the influence of particle filter parameters on order effects in causal learning (2011) (33)
Deconfounding hypothesis generation and evaluation in Bayesian models (2010) (33)
Probabilistic models of cognitive development: Towards a rational constructivist approach to the study of learning and development (2011) (33)
Analyzing human feature learning as nonparametric Bayesian inference (2008) (33)
Empirical evidence for resource-rational anchoring and adjustment (2018) (32)
Predicting human decisions with behavioral theories and machine learning (2019) (32)
Inferring Learners' Knowledge From Their Actions (2015) (32)
nbgrader: A Tool for Creating and Grading Assignments in the Jupyter Notebook (2019) (32)
Improved Reconstruction of Protolanguage Word Forms (2009) (31)
When to use which heuristic: A rational solution to the strategy selection problem (2015) (31)
The high availability of extreme events serves resource-rational decision-making (2014) (31)
A Rational Account of the Perceptual Magnet Effect (2007) (31)
Why are people bad at detecting randomness? A statistical argument. (2013) (30)
Structure and Flexibility in Bayesian Models of Cognition (2015) (30)
What can mathematical, computational and robotic models tell us about the origins of syntax? (2009) (28)
Sensitivity to Shared Information in Social Learning (2018) (28)
Evaluating computational models of explanation using human judgments (2013) (27)
From Algorithmic to Subjective Randomness (2003) (27)
Empirical Evidence for Markov Chain Monte Carlo in Memory Search (2014) (26)
A Probabilistic Approach to Language Change (2007) (26)
A rational model of the Dunning–Kruger effect supports insensitivity to evidence in low performers (2021) (26)
Competing strategies in categorization: expediency and resistance to knowledge restructuring. (2000) (25)
Identifying expectations about the strength of causal relationships (2015) (25)
Learning Rewards from Linguistic Feedback (2020) (24)
A rational model of the effects of distributional information on feature learning (2011) (24)
Generating Plans that Predict Themselves (2018) (24)
Thirty years of Marr's Vision: Levels of Analysis in Cognitive Science (2015) (24)
Approximating Bayesian inference with a sparse distributed memory system (2013) (23)
Constructing a hypothesis space from the Web for large-scale Bayesian word learning (2012) (23)
Evolution in Mind: Evolutionary Dynamics, Cognitive Processes, and Bayesian Inference (2017) (23)
Learning to select computations (2017) (22)
Technical Introduction: A primer on probabilistic inference (2008) (22)
Relevant and Robust (2015) (22)
A Probabilistic Model of Meetings That Combines Words and Discourse Features (2008) (21)
The value of abstraction (2019) (21)
Testing the Efficiency of Markov Chain Monte Carlo With People Using Facial Affect Categories (2012) (20)
A multidimensional scaling approach to mental multiplication (2002) (20)
Revealing human inductive biases for category learning by simulating cultural transmission (2014) (20)
A Bayesian Model of Rule Induction in Raven's Progressive Matrices (2012) (20)
Learning hypothesis spaces and dimensions through concept learning (2010) (20)
A Bayesian framework for modeling intuitive dynamics (2009) (20)
Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning (2009) (20)
Subjective randomness and natural scene statistics (2010) (20)
From partners to populations: A hierarchical Bayesian account of coordination and convention (2021) (20)
Modeling human categorization of natural images using deep feature representations (2017) (18)
Elements of a rational framework for continuous-time causal induction (2012) (18)
The nested Chinese restaurant process and Bayesian inference of topic hierarchies (2007) (18)
A Nonparametric Bayesian Model of Multi-Level Category Learning (2011) (18)
Scaling up psychology via Scientific Regret Minimization (2020) (17)
Segmenting and Recognizing Human Action using Low-level Video Features (2011) (17)
Compositionality in rational analysis: grammar-based induction for concept learning (2008) (17)
Subjective randomness as statistical inference (2018) (17)
Rational use of cognitive resources in human planning (2022) (17)
Cognitive prostheses for goal achievement (2019) (17)
Learning invariant features using the Transformed Indian Buffet Process (2010) (17)
Distributional Cues to Word Boundaries: Context is Important (2008) (16)
When children are better learners than adults: Developmental differences in learning the forms of causal relationships (2010) (16)
A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments (2006) (16)
Universal linguistic inductive biases via meta-learning (2020) (16)
Learners Use Word-Level Statistics in Phonetic Category Acquisition (2011) (16)
Testing a Bayesian Measure of Representativeness Using a Large Image Database (2011) (16)
Serial reproduction reveals the geometry of visuospatial representations (2021) (16)
Greater learnability is not sufficient to produce cultural universals (2013) (16)
Learning from Actions and their Consequences: Inferring Causal Variables from Continuous Sequences of Human Action (2009) (15)
Estimating human priors on causal strength (2011) (15)
Preschoolers’ understanding of graded preferences (2015) (15)
A rational model of causal induction with continuous causes (2011) (15)
Convergence Bounds for Language Evolution by Iterated Learning (2009) (15)
Human biases limit cumulative innovation (2021) (15)
Modeling Cross-Domain Causal Learning in Preschoolers as Bayesian Inference (2006) (15)
Bayesian collective learning emerges from heuristic social learning (2021) (15)
Using Inverse Planning for Personalized Feedback (2016) (15)
People construct simplified mental representations to plan (2021) (14)
Rethinking language: How probabilities shape the words we use (2011) (14)
When Does Bounded-Optimal Metareasoning Favor Few Cognitive Systems? (2017) (14)
Upsetting the contingency table: Causal induction over sequences of point events (2015) (14)
Understanding Human Intelligence through Human Limitations (2020) (14)
Optimally Designing Games for Cognitive Science Research (2012) (14)
Do I know that you know what you know? Modeling testimony in causal inference (2012) (14)
Some specifics about generalization (2001) (13)
Algorithms to live by (2020) (13)
When does the majority rule? Preschoolers' trust in majority informants varies by task domain (2013) (13)
Bayesian nonparametric latent feature models (with discussion) (2006) (13)
A graph-theoretic approach to multitasking (2016) (13)
Parallelograms revisited: Exploring the limitations of vector space models for simple analogies (2020) (13)
From convolutional neural networks to models of higher‐level cognition (and back again) (2021) (13)
Modeling Human Performance on Statistical Word Segmentation Tasks (2007) (13)
The nested Chinese restaurant process and hierarchical topic models (2007) (13)
Can children balance the size of a majority with the quality of their information? (2015) (13)
Children search for information as efficiently as adults, but seek additional confirmatory evidence (2015) (12)
Understanding exploration in humans and machines by formalizing the function of curiosity (2020) (12)
The Efficiency of Human Cognition Reflects Planned Information Processing (2020) (12)
Capturing human categorization of natural images at scale by combining deep networks and cognitive models (2019) (12)
Formal Approaches in Categorization: Nonparametric Bayesian models of categorization (2011) (12)
What to simulate? Inferring the right direction for mental rotation (2014) (12)
End-to-end Deep Prototype and Exemplar Models for Predicting Human Behavior (2020) (12)
Analyzing the Rate at Which Languages Lose the Influence of a Common Ancestor (2014) (12)
A rational reinterpretation of dual-process theories (2021) (12)
Human planning as optimal information seeking (2021) (12)
A rational analysis of confirmation with deterministic hypotheses (2008) (11)
Revealing ontological commitments by magic (2015) (11)
Identifying representations of categories of discrete items using Markov chain Monte Carlo with People (2012) (11)
Exploring Human Cognition Using Large Image Databases (2016) (11)
Object Representations as Fixed Points: Training Iterative Refinement Algorithms with Implicit Differentiation (2022) (11)
Preschoolers sample from probability distributions (2010) (11)
Generalizing meanings from partners to populations: Hierarchical inference supports convention formation on networks (2020) (11)
Reconstructing the cascade of language processing in the brain using the internal computations of a transformer-based language model (2023) (11)
When Absence of Evidence Is Evidence of Absence: Rational Inferences From Absent Data. (2017) (11)
Statistics and the Bayesian mind (2006) (11)
Bayesian models as tools for exploring inductive biases (2011) (10)
Anchoring and Adjustment (2017) (10)
Competing strategies in categorization : Expediency and resistance to knowledge restructuring (2000) (10)
Leveraging artificial intelligence to improve people’s planning strategies (2022) (10)
Probabilistic models of cognition 1 Running head : PROBABILISTIC MODELS OF COGNITION Probabilistic models of cognition : Exploring the laws of thought (2009) (10)
Word forms - not just their lengths- are optimized for efficient communication (2017) (10)
Resource-rational Task Decomposition to Minimize Planning Costs (2020) (10)
Cognitive science as a source of forward and inverse models of human decisions for robotics and control (2021) (10)
The Effects of Cultural Transmission Are Modulated by the Amount of Information Transmitted (2013) (10)
Investigating Representations of Verb Bias in Neural Language Models (2020) (10)
Replicating Color Term Universals through Human Iterated Learning (2010) (9)
Discovering Rational Heuristics for Risky Choice (2022) (9)
Bayesian Models of Inductive Learning (2006) (9)
Learning Hierarchical Visual Representations in Deep Neural Networks Using Hierarchical Linguistic Labels (2018) (9)
PrAGMATiC: a Probabilistic and Generative Model of Areas Tiling the Cortex (2015) (9)
Inferring learners' knowledge from observed actions (2012) (9)
Online gradient-based mixtures for transfer modulation in meta-learning (2018) (9)
Teacakes, Trains, Taxicabs and Toxins: A Bayesian Account of Predicting the Future (2000) (8)
Revealing Priors on Category Structures Through Iterated Learning (2006) (8)
Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions (2020) (8)
Extending rational models of communication from beliefs to actions (2021) (8)
Modeling Individual Differences with Dirichlet Processes (2005) (7)
Modulating transfer between tasks in gradient-based meta-learning (2018) (7)
Exploring the Relationship Between Learnability and Linguistic Universals (2011) (7)
A computational process-tracing method for measuring people's planning strategies and how they change over time. (2022) (7)
Optimally designing games for behavioural research (2014) (7)
The Rational Basis of Representatives (2001) (7)
Passive attention in artificial neural networks predicts human visual selectivity (2021) (7)
Predicting focal colors with a rational model of representativeness (2012) (7)
Topics in semantic association (2005) (7)
Extracting low-dimensional psychological representations from convolutional neural networks (2020) (7)
Distributional cues to word segmentation: Context is important (2007) (7)
How Can Memory-Augmented Neural Networks Pass a False-Belief Task? (2017) (7)
Learning the Functional Form of Causal Relationships (2007) (6)
Experimental evolutionary simulations of learning, memory and life history (2020) (6)
Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment (2021) (6)
Why are People Bad at Detecting Randomness? Because it is Hard (2008) (6)
How do you know that? Sensitivity to statistical dependency in social learning (2013) (6)
The Challenges of Large-Scale, Web-Based Language Datasets: Word Length and Predictability Revisited (2021) (6)
Structure and strength 1 Running head : STRUCTURE AND STRENGTH Structure and strength in causal induction (2005) (6)
Words are all you need? Capturing human sensory similarity with textual descriptors (2022) (6)
Connecting human and machine learning via probabilistic models of cognition (2009) (6)
Learning a face space for experiments on human identity (2018) (6)
Using Machine Learning to Guide Cognitive Modeling: A Case Study in Moral Reasoning (2019) (6)
Optimal Language Learning: The Importance of Starting Representative (2010) (6)
Adding population structure to models of language evolution by iterated learning (2017) (6)
Advancing rational analysis to the algorithmic level (2020) (6)
Intuitions about magic track the development of intuitive physics (2021) (5)
The effect of distributional information on feature learning (2009) (5)
Using Vocabulary Knowledge in Bayesian Multinomial Estimation (2001) (5)
Complex cognitive algorithms preserved by selective social learning in experimental populations (2022) (5)
Rational randomness: the role of sampling in an algorithmic account of preschooler's causal learning. (2012) (5)
A rational model of people’s inferences about others’ preferences based on response times (2021) (5)
Is Holism A Problem For Inductive Inference? A Computational Analysis (2014) (5)
How memory biases affect information transmission: A rational analysis of serial reproduction (2008) (5)
Exploiting Attention to Reveal Shortcomings in Memory Models (2018) (5)
Inferring mass in complex physical scenes via probabilistic simulation (2013) (5)
Sampling Assumptions Affect Use of Indirect Negative Evidence in Language Learning (2016) (5)
Identifying category representations for complex stimuli using discrete Markov chain Monte Carlo with people (2019) (4)
A Bounded Rationality Account of Wishful Thinking (2014) (4)
How to Be Helpful to Multiple People at Once (2020) (4)
Adaptive Sampling for Convex Regression (2018) (4)
A formal analysis of cultural evolution by replacement (2008) (4)
Uncovering visual priors in spatial memory using serial reproduction (2017) (4)
The pursuit of happiness: A reinforcement learning perspective on habituation and comparisons (2022) (4)
Children's Imitation of Action Sequences is Influenced by Statistical Evidence and Inferred Causal Structure (2010) (4)
Comparing the inductive biases of simple neural networks and Bayesian models (2012) (4)
Rethinking experiment design as algorithm design (2016) (4)
Disentangling Abstraction from Statistical Pattern Matching in Human and Machine Learning (2022) (4)
Capturing human category representations by sampling in deep feature spaces (2018) (4)
A Bayesian model of navigation in squirrels (2011) (4)
Assessing Mathematics Misunderstandings via Bayesian Inverse Planning (2020) (4)
Formalizing Prior Knowledge in Causal Induction (2017) (4)
What the Baldwin Effect affects depends on the nature of plasticity (2020) (4)
Distinguishing rule- and exemplar-based generalization in learning systems (2021) (4)
Modelling minds as well as populations (2011) (4)
Design from Zeroth Principles (2016) (4)
Generative and Discriminative Models in Cognitive Science (2015) (3)
Linguistic communication as (inverse) reward design (2022) (3)
Data-Driven, Photorealistic Social Face-Trait Encoding, Prediction, and Manipulation Using Deep Neural Networks (2020) (3)
Globally Inaccurate Stereotypes Can Result From Locally Adaptive Exploration (2022) (3)
The Emergence of Collective Structures Through Individual Interactions (2009) (3)
Predicting Human Similarity Judgments Using Large Language Models (2022) (3)
What the Baldwin Effect affects (2015) (3)
A HUMAN MODEL OF COLOR TERM EVOLUTION (2008) (3)
Evidence for the size principle in semantic and perceptual domains (2017) (3)
Shades of confusion: Lexical uncertainty modulates ad hoc coordination in an interactive communication task (2021) (3)
Empirical tests of large-scale collaborative recall (2017) (3)
Human Priors in Hierarchical Program Induction (2018) (3)
An ideal observer model for identifying the reference frame of objects (2011) (3)
Control of mental representations in human planning (2021) (3)
On the Informativeness of Supervision Signals (2022) (3)
Can Humans Do Less-Than-One-Shot Learning? (2022) (3)
Using Natural Language and Program Abstractions to Instill Human Inductive Biases in Machines (2022) (3)
Interpreting Freeform Equation Solving (2015) (3)
Compositionality in rational analysis (2008) (3)
Multitasking Capacity: Hardness Results and Improved Constructions (2018) (3)
Meta-Learning of Structured Task Distributions in Humans and Machines (2020) (3)
What Language Reveals about Perception: Distilling Psychophysical Knowledge from Large Language Models (2023) (3)
Caching Algorithms and Rational Models of Memory (2014) (3)
Latent Feature Models for Link Prediction (2009) (3)
Connecting Context-specific Adaptation in Humans to Meta-learning. (2020) (2)
If it's important, then I’m curious: Increasing perceived usefulness stimulates curiosity (2020) (2)
Shaping Model-Free Reinforcement-Learning with Model-Based Pseudorewards (2018) (2)
Exploiting Effective Representations for Chinese Sentiment Analysis Using a Multi-Channel Convolutional Neural Network (2018) (2)
Diagnosing Algebra Understanding via Bayesian Inverse Planning (2014) (2)
Overcoming Individual Limitations Through Distributed Computation: Rational Information Accumulation in Multigenerational Populations (2022) (2)
Optimal policies for free recall. (2021) (2)
Humans decompose tasks by trading off utility and computational cost (2022) (2)
A learned generative model of faces for experiments on human identity (2018) (2)
Discovering Inductive Biases in Categorization through Iterated Learning (2011) (2)
A Bayesian Analysis of Serial Reproduction (2007) (2)
The experimental evolution of human culture: flexibility, fidelity and environmental instability (2022) (2)
The Computational Challenges of Pursuing Multiple Goals: Network Structure of Goal Systems Predicts Human Performance (2018) (2)
Analogy as Nonparametric Bayesian Inference over Relational Systems (2020) (2)
A reward shaping method for promoting metacognitive learning (2017) (2)
Memory transmission in small groups and large networks: An empirical study (2021) (2)
Look-Ahead Monte Carlo with People (2012) (2)
Cultural evolution with sparse testimony: when does the cultural ratchet slip? (2014) (2)
Preschoolers rationally sample hypotheses (2010) (2)
Probing BERT’s priors with serial reproduction chains (2022) (2)
Evaluating models of robust word recognition with serial reproduction (2021) (2)
The strengths of – and some of the challenges for – Bayesian models of cognition (2009) (2)
Meta-Learning of Compositional Task Distributions in Humans and Machines (2020) (2)
errors adaptation deficits with large and small visuomotor Individuals with cerebellar degeneration show similar (2013) (1)
The Rational Basis of Representatives - eScholarship (2001) (1)
A More Rational Model of Categorization - eScholarship (2006) (1)
Hypothesis Generation (2020) (1)
Elemental causal induction 1 Running head: ELEMENTAL CAUSAL INDUCTION Elemental causal induction (2004) (1)
Visually-Grounded Bayesian Word Learning (2012) (1)
Uncovering mental representations with Markov chain (2010) (1)
Wallace: Automating Cultural Evolution Experiments Through Crowdsourcing (2016) (1)
Utility-weighted sampling in decisions from experience (2015) (1)
Predicting Word Learning in Children from the Performance of Computer Vision Systems (2022) (1)
Bayesian generalization with circular consequential regions (2012) (1)
Understanding how people learn the features of objects as Bayesian inference (2010) (1)
How to talk so AI will learn: Instructions, descriptions, and autonomy (2022) (1)
A Bayesian Framework for Learning Words From Multiword Utterances (2015) (1)
The anchoring bias reflects rational use of cognitive resources (2017) (1)
Analyzing Diffusion as Serial Reproduction (2022) (1)
Scaling up Psychology via Scientific Regret Minimization: A Case Study in Moral Decisions (2019) (1)
Superhuman Artificial Intelligence Can Improve Human Decision Making by Increasing Novelty (2023) (1)
Technical Introduction: A primer on probabilistic inference - eScholarship (2006) (1)
A rational model of causal inference with continuous causes (2011) (1)
Bayesian Approaches to Color Category Learning (2021) (1)
Neural Constraint Satisfaction: Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement (2023) (1)
researchdesigning games for behavioural (2014) (1)
Learning to generalize like humans using basic-level object labels (2019) (1)
Rational Process Models (2009) (1)
How to talk so your robot will learn: Instructions, descriptions, and pragmatics (2022) (1)
Alignment with human representations supports robust few-shot learning (2023) (1)
Modeling human eye movements during immersive visual search (2022) (1)
Sampling from object and scene representations using deep feature spaces (2018) (1)
Exploring the structure of mental representations by implementing computer algorithms with people (2015) (1)
People Do Not Just Plan, They Plan to Plan (2020) (1)
FROM HEURISTIC TO OPTIMAL MODELS IN NATURALISTIC VISUAL SEARCH (2020) (1)
Correction: The Sapir-Whorf Hypothesis and Probabilistic Inference: Evidence from the Domain of Color (2016) (0)
The Efficiency of Human Cognition Reflects Planned Use of Information Processing (2019) (0)
( YIP-10 ) FAST , FLEXIBLE , RATIONAL INDUCTIVE INFERENCE (2013) (0)
child as a rational model of preference understanding in children. (2014) (0)
From mere coincidences to meaningful discoveries q (2006) (0)
Cultural Evolution of Language: Implications for Cognitive Science (2009) (0)
Title: Individuals with Cerebellar Degeneration Show Similar Adaptation Deficits with Large and Small 1 Visuomotor Errors. 2 3 4 5 (2012) (0)
Sparse Skill Coding: Learning Behavioral Hierarchies with Sparse Codes (2019) (0)
Beyond Playing 20 Questions with Nature: Integrative Experiment Design in the Social and Behavioral Sciences. (2022) (0)
Multitasking Capacity: Hardness Results and Improved Constructions | SIAM Journal on Discrete Mathematics | Vol. 34, No. 1 | Society for Industrial and Applied Mathematics (2020) (0)
Probability Primer 1 Running head: PROBABILITY PRIMER A Primer on Probabilistic Inference (2007) (0)
Running head : EVERYDAY PREDICTIONS Optimal predictions in everyday cognition (2005) (0)
Bias amplification in experimental social networks is reduced by resampling (2022) (0)
The Telephone Game: Exploring Inductive Biases In Naturalistic Language Use (2014) (0)
Empirical evidence for resource-rational anchoring and adjustment (2017) (0)
From coincidences to discoveries 1 Running head : From coincidences to discoveries From mere coincidences to meaningful discoveries (2006) (0)
Scaling up Psychology via Scientific Regret Minimization: A Case Study in Moral Decision-Making (2019) (0)
Using features from deep neural networks to model human categorization of natural images (2018) (0)
Stress, intertemporal choice, and mitigation behavior during the COVID-19 pandemic. (2022) (0)
A rational model of sequential self-assessment (2020) (0)
Rejoinder for “ Bayesian Nonparametric Latent Feature Models (2007) (0)
Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics (2007) (0)
Symposium: Grow your own representations: Computational constructivism (2011) (0)
Connecting input filtering and selection in language evolution (2012) (0)
Spatial memory biases reflect encoding precision and not categorical perception (2019) (0)
Life History and Learning : Changes in cognitive flexibility and hypothesis search from childhood to adolescence to adulthood (2017) (0)
O BJECT -C ENTRIC L EARNING AS N ESTED O PTIMIZATION (2022) (0)
The virtuous cycle of theory-building: Improving theoretical understanding in the (online) lab and in the wild (2018) (0)
Learning How to Generalize (2019) (0)
From preferences to choices and back again: evidence for human inconsistency and its implications (2011) (0)
Recommendation as generalization: Using big data to evaluate cognitive models. (2020) (0)
Fast, Flexible, Rational Inductive Inference (2013) (0)
Correspondences between word learning in children and captioning models (2022) (0)
Show or tell? Exploring when (and why) teaching with language outperforms demonstration (2022) (0)
How to talk so your AI will learn: Instructions, descriptions, and autonomy (2022) (0)
RUNNING HEAD : STRATEGY SELECTION AS RATIONAL METAREASONING Strategy selection as rational metareasoning (2017) (0)
Rational Heuristics for One-Shot Games ∗ (2021) (0)
Symposium: The emergence of collective structure through individual interactions (2009) (0)
ESSEX BUSINESS SCHOOL Financial Crisis and the Silence of the Auditors (2009) (0)
Categorization as nonparametric Bayesian density estimation 1 Running head: CATEGORIZATION AS NONPARAMETRIC BAYESIAN DENSITY ESTIMATION Categorization as nonparametric Bayesian density estimation (2007) (0)
Learning to Be (In)variant: Combining Prior Knowledge and Experience to Infer Orientation Invariance in Object Recognition. (2017) (0)
Developmental and computational perspectives on infant social cognition (2010) (0)
Running head : RANDOMNESS AS INFERENCE 1 Subjective randomness as statistical inference (2018) (0)
Generation and Evaluation in Bayesian Models (2010) (0)
MonkeysLesions and Prism Adaptation in Macaque (2015) (0)
Proceedings of the 33th Annual Meeting of the Cognitive Science Society, CogSci 2011, Boston, Massachusetts, USA, July 20-23, 2011 (2011) (0)
Learning from others: Adult and child strategies in assessing conflicting ratings (2015) (0)
Structure and strength in causal induction q (2005) (0)
Testing a rational account of pragmatic reasoning : The case of spatial relations Cognitive (2015) (0)
McKenzie : Challenges to rational process models (2009) (0)
Revealing human inductive biases for category learning by simulating cultural transmission (2014) (0)
Context-Conditioning as Cognitive Control: Guiding Meta-learning with Task Information (2020) (0)
Structure & Priors in Reinforcement Learning (SPiRL) (2019) (0)
Young Toddlers' Understanding of Graded Preferences (2011) (0)
Structure and strength in causal judgments (2003) (0)
Proceedings of the 34th Annual Meeting of the Cognitive Science Society, CogSci 2012, Sapporo, Japan, August 1-4, 2012 (2012) (0)
Competition in Cross-situational Word Learning: A Computational Study (2020) (0)
Using Natural Language to Guide Meta-Learning Agents towards Human-like Inductive Biases (2022) (0)
Evolutionary consequences of learning, culture and complex behaviors (2016) (0)
Optimally Designing Games for Cognitive Science Research - eScholarship (2012) (0)
Cognitive prostheses for goal achievement (2019) (0)
Why are people bad at detecting randomness ? A statistical analysis (2012) (0)
A rational model of function learning (2015) (0)
Moot Point Process Models (2014) (0)
Identifying category representations for complex stimuli using discrete Markov chain Monte Carlo with people (2019) (0)
Human uncertainty improves object classification (2019) (0)
A Pragmatic Account of the Weak Evidence Effect (2021) (0)
Competing Strategies in Categorization (2000) (0)
Active Learning for Convex Regression (2017) (0)
Special Issue : Probabilistic models of cognition Probabilistic inference in human semantic memory (2006) (0)
IMPLICIT DIFFERENTIATION (2002) (0)
Comparing Methods for Identifying Categories 2 (2011) (0)
Retrieving Effectively from Memory (REM) (2006) (0)
Culture on a chip (UC Berkeley) (2016) (0)
nbgrader v0.5.5 (2019) (0)
Explore-Exploit Tradeoffs Generate Cascading Societal Stereotypes (2022) (0)
UMAN P RIORS FOR P LAYING V IDEO G AMES (2018) (0)
Confirmation for Deterministic Hypotheses 1 Running head : CONFIRMATION FOR DETERMINISTIC HYPOTHESES Seeking Confirmation is Rational for Deterministic Hypotheses (2010) (0)
A Primer on Probabilistic Inference - eScholarship (2006) (0)
Grow your own representations: Computational constructivism (2011) (0)
Caching Algorithms and Rational Models of Memory - eScholarship (2014) (0)
A walk through face space: Affect classification using Markov chain Monte Carlo (2009) (0)
Improving machine classification using human uncertainty measurements (2018) (0)
Global Decision-Making via Local Economic Transactions (2020) (0)
How do Humans Overcome Individual Computational Limitations by Working Together? (2023) (0)
O BJECT R EPRESENTATIONS AS E QUILIBRIA : T RAINING I TERATIVE I NFERENCE A LGORITHMS WITH I MPLICIT D IFFERENTIATION (2022) (0)
Determining people's expectations about the form of causal relationships (2012) (0)
Children and adults differ in their strategies for social learning (2015) (0)
in semantic representation (2006) (0)
Leveraging deep neural networks to capture psychological representations (2017) (0)
Memory transmission in small groups and large networks: An empirical study (2021) (0)
Publisher Correction: Rational use of cognitive resources in human planning (2022) (0)
The Computational Structure of Unintentional Meaning (2019) (0)
A face you can trust: Iterated learning reveals how stereotypes of facial trustworthiness may propagate in the absence of evidence (2020) (0)
Inaccurate Stereotypes from Rational Exploration (2021) (0)
Intertemporal choice under stress: an ongoing study during the COVID-19 pandemic (2020) (0)
Questions for future research (2006) (0)
Simulating the transmission of systems of color terms in the laboratory (2010) (0)
Optimal planning to plan: People partially plan based on plan specificity (2019) (0)
Gaussian process surrogate models for neural networks (2022) (0)
Running Head : BAYES AND BLICKETS Bayes and blickets : Effects of knowledge on causal induction in children and adults (2011) (0)
Show or Tell? Demonstration is More Robust to Changes in Shared Perception than Explanation (2020) (0)
Iterated learning reveals stereotypes of facial trustworthiness that propagate in the absence of evidence (2023) (0)
ynamic Causal Learning (2002) (0)
Probabilistic Inference Using Stored Examples (2006) (0)
NEUTRAL MODELS FOR LANGUAGE EVOLUTION (2012) (0)
Chapter 15 Rational Analysis as a Link between Human Memory and Information Retrieval (2007) (0)
Theory-based Bayesian Models of Inductive Inference (2010) (0)
Learning to Learn Functions (2023) (0)
Arengiya Anyainya Aidmeniya Aburliya Adardiya Agngiya Aweniya Amaidya Abmarliya Awaadya Anguriya Adiaya Angeliya Algyeliya Adniadya Aleriya Umbaidya Anowadya Muriya Angenduriya Amburniya Andungiya Aneriya Aiyenga Undyaidya Gnaldena (2004) (0)
A Hierarchical Bayesian Model for Topic Segmentation (2005) (0)
Finding the traces of behavioral and cognitive processes in big data and naturally occurring datasets (2017) (0)
Extended Abstract: Concept Acquisition Through Meta-Learning (2017) (0)
Words are all you need? Language as an approximation for human similarity judgments (2022) (0)
Modeling visual search in naturalistic virtual reality environments (2020) (0)

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