BLUElink> Development of Operational Oceanography and Servicing in Australia. - Gary G. Brassington; Tim Pugh; Claire Spillman; Eric Schulz; Helen Beggs; Andreas Schiller; Peter R. Oke (J. Res. Pract. Inf. Technol., 2007)

Predict choice: A comparison of 21 mathematical models. - Eric Schulz; Maarten Speekenbrink; David R. Shanks (CogSci, 2014)

Active learning as a means to distinguish among prominent decision strategies. - Paula Parpart; Eric Schulz; Maarten Speekenbrink; Bradley C. Love (CogSci, 2015)

Learning and decisions in contextual multi-armed bandit tasks. - Eric Schulz; Emmanouil Konstantinidis; Maarten Speekenbrink (CogSci, 2015)

Assessing the Perceived Predictability of Functions. - Eric Schulz; Joshua B. Tenenbaum; David N. Reshef; Maarten Speekenbrink; Samuel Gershman (CogSci, 2015)

Better safe than sorry: Risky function exploitation through safe optimization. - Eric Schulz; Quentin J. M. Huys; Dominik R. Bach; Maarten Speekenbrink; Andreas Krause 001 (CogSci, 2016)

Simple trees in complex forests: Growing Take The Best by Approximate Bayesian Computation. - Eric Schulz; Maarten Speekenbrink; Björn Meder (CogSci, 2016)

Probing the Compositionality of Intuitive Functions. - Eric Schulz; Josh Tenenbaum 001; David Duvenaud; Maarten Speekenbrink; Samuel J. Gershman (NIPS, 2016)

Amortized Hypothesis Generation. - Ishita Dasgupta 001; Eric Schulz; Noah D. Goodman; Samuel J. Gershman (CogSci, 2017)

Strategic exploration in human adaptive control. - Eric Schulz; Edgar D. Klenske; Neil Bramley; Maarten Speekenbrink (CogSci, 2017)

It is new, but will it be good? Context-driven exploration of novel options. - Hrvoje Stojic; Eric Schulz; Maarten Speekenbrink (CogSci, 2017)

Mapping the unknown: The spatially correlated multi-armed bandit. - Charley M. Wu; Eric Schulz; Maarten Speekenbrink; Jonathan D. Nelson; Björn Meder (CogSci, 2017)

Learning as program induction. - Neil Bramley; Eric Schulz; Fei Xu; Josh Tenenbaum 001 (CogSci, 2018)

Learning to act by integrating mental simulations and physical experiments. - Ishita Dasgupta 001; Kevin A. Smith 001; Eric Schulz; Josh Tenenbaum 001; Samuel Gershman (CogSci, 2018)

Active Function Learning. - Angela Jones; Eric Schulz; Björn Meder; Azzurra Ruggeri (CogSci, 2018)

Adaptive planning in human search. - Moritz Krusche; Eric Schulz; Arthur Guez; Maarten Speekenbrink (CogSci, 2018)

Is covariance ignorance responsible for the success of heuristics? - Paula Parpart; Eric Schulz (CogSci, 2018)

Learning list concepts through program induction. - Joshua S. Rule; Eric Schulz; Steven T. Piantadosi; Josh Tenenbaum 001 (CogSci, 2018)

Connecting conceptual and spatial search via a model of generalization. - Charley M. Wu; Eric Schulz; Mona M. Garvert; Björn Meder; Nicolas W. Schuck (CogSci, 2018)

Generalization and Search in Risky Environments. - Eric Schulz; Charley M. Wu; Quentin J. M. Huys; Andreas Krause 001; Maarten Speekenbrink (Cogn. Sci., 2018)

Masterminding in Education: Bringing cognition, emotion and motivation together in a unified mathematical framework. - Lara Bertram; Eric Schulz; Elif Özel; Matthias Hofer 002; Laura Martignon; Jonathan D. Nelson (CogSci, 2019)

Heuristics, hacks, and habits: Boundedly optimal approaches to learning, reasoning and decision making. - Ishita Dasgupta 001; Eric Schulz; Jessica B. Hamrick; Josh Tenenbaum 001 (CogSci, 2019)

Exploring the space of human exploration using Entropy Mastermind. - Eric Schulz; Lara Bertram; Matthias Hofer 002; Jonathan D. Nelson (CogSci, 2019)

Generalization as diffusion: human function learning on graphs. - Charley M. Wu; Eric Schulz; Samuel Gershman (CogSci, 2019)

Under pressure: The influence of time limits on human exploration. - Charley M. Wu; Eric Schulz; Kimberly Gerbaulet; Timothy J. Pleskac; Maarten Speekenbrink (CogSci, 2019)

The Psychology of Human Entropy Intuitions. - Lara Bertram; Eric Schulz; Matthias Hofer 002; Jonathan D. Nelson (CogSci, 2020)

Learning sequential patterns from graphical programs. - Anselm Rothe; Eric Schulz; Mathias Sablé-Meyer; Josh Tenenbaum 001; Azzurra Ruggeri (CogSci, 2020)

Similarities and differences in spatial and non-spatial cognitive maps. - Charley M. Wu; Eric Schulz; Mona M. Garvert; Björn Meder; Nicolas W. Schuck (PLoS Comput. Biol., 2020)

Correction: Similarities and differences in spatial and non-spatial cognitive maps. - Charley M. Wu; Eric Schulz; Mona M. Garvert; Björn Meder; Nicolas W. Schuck (PLoS Comput. Biol., 2020)

Using Games to Understand Intelligence. - Franziska Brändle; Kelsey R. Allen; Josh Tenenbaum 001; Eric Schulz (CogSci, 2021)

How does mental sorting scale? - Susanne Haridi; Charley M. Wu; Ishita Dasgupta 001; Eric Schulz (CogSci, 2021)

Compositional generalization in multi-armed bandits. - Tankred Saanum; Eric Schulz; Maarten Speekenbrink (CogSci, 2021)

Chunking as a Rational Solution to the Speed-Accuracy Trade-off in a Serial Reaction Time Task. - Shuchen Wu; Noémi Élteto; Ishita Dasgupta 001; Eric Schulz (CogSci, 2021)

Connecting Exploration, Generalization, and Planning in Correlated Trees. - Tobias Ludwig 003; Charley M. Wu; Eric Schulz (CogSci, 2022)

Fun as maximizing learnability: Balancing difficulty and prior knowledge. - Franziska Brändle; Charley M. Wu; Eric Schulz (CogSci, 2022)

Decision-Making with Naturalistic Options. - Can Demircan; Leonardo Pettini; Tankred Saanum; Marcel Binz; Blazej M. Baczkowski; Christian F. Doeller; Mona M. Garvert; Eric Schulz (CogSci, 2022)

Modeling Human Exploration Through Resource-Rational Reinforcement Learning. - Marcel Binz; Eric Schulz (NeurIPS, 2022)

Learning Structure from the Ground up - Hierarchical Representation Learning by Chunking. - Shuchen Wu; Noémi Élteto; Ishita Dasgupta 001; Eric Schulz (NeurIPS, 2022)

Exploration With a Finite Brain. - Marcel Binz; Eric Schulz (CoRR, 2022)

Using cognitive psychology to understand GPT-3. - Marcel Binz; Eric Schulz (CoRR, 2022)

Stochastic Gradient Descent Captures How Children Learn About Physics. - Luca M. Schulze Buschoff; Eric Schulz; Marcel Binz (CoRR, 2022)

Learning Parsimonious Dynamics for Generalization in Reinforcement Learning. - Tankred Saanum; Eric Schulz (CoRR, 2022)

The Acquisition of Physical Knowledge in Generative Neural Networks. - Luca M. Schulze Buschoff; Eric Schulz; Marcel Binz (ICML, 2023)

Meta-in-context learning in large language models. - Julian Coda-Forno; Marcel Binz; Zeynep Akata; Matt M. Botvinick; Jane X. Wang; Eric Schulz (NeurIPS, 2023)

Reinforcement Learning with Simple Sequence Priors. - Tankred Saanum; Noémi Élteto; Peter Dayan; Marcel Binz; Eric Schulz (NeurIPS, 2023)

In-Context Impersonation Reveals Large Language Models' Strengths and Biases. - Leonard Salewski; Stephan Alaniz; Isabel Rio-Torto; Eric Schulz; Zeynep Akata (NeurIPS, 2023)

Meta-Learned Models of Cognition. - Marcel Binz; Ishita Dasgupta 001; Akshay K. Jagadish; Matthew M. Botvinick; Jane X. Wang; Eric Schulz (CoRR, 2023)

Inducing anxiety in large language models increases exploration and bias. - Julian Coda-Forno; Kristin Witte; Akshay K. Jagadish; Marcel Binz; Zeynep Akata; Eric Schulz (CoRR, 2023)

Playing repeated games with Large Language Models. - Elif Akata; Lion Schulz; Julian Coda-Forno; Seong Joon Oh; Matthias Bethge; Eric Schulz (CoRR, 2023)

Language Aligned Visual Representations Predict Human Behavior in Naturalistic Learning Tasks. - Can Demircan; Tankred Saanum; Leonardo Pettini; Marcel Binz; Blazej M. Baczkowski; Paula Kaanders; Christian F. Doeller; Mona M. Garvert; Eric Schulz (CoRR, 2023)

Have we built machines that think like people? - Luca M. Schulze Buschoff; Elif Akata; Matthias Bethge; Eric Schulz (CoRR, 2023)

How should the advent of large language models affect the practice of science? - Marcel Binz; Stephan Alaniz; Adina Roskies; Balazs Aczel; Carl T. Bergstrom; Colin Allen; Daniel Schad; Dirk U. Wulff; Jevin D. West; Qiong Zhang; Richard M. Shiffrin; Samuel J. Gershman; et al. (CoRR, 2023)

Turning large language models into cognitive models. - Marcel Binz; Eric Schulz (ICLR, 2024)

CogBench: a large language model walks into a psychology lab. - Julian Coda-Forno; Marcel Binz; Jane X. Wang; Eric Schulz (ICML, 2024)

Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks. - Akshay K. Jagadish; Julian Coda-Forno; Mirko Thalmann; Eric Schulz; Marcel Binz (ICML, 2024)

In-Context Learning Agents Are Asymmetric Belief Updaters. - Johannes A. Schubert; Akshay K. Jagadish; Marcel Binz; Eric Schulz (ICML, 2024)

Evaluating alignment between humans and neural network representations in image-based learning tasks. - Can Demircan; Tankred Saanum; Leonardo Pettini; Marcel Binz; Blazej M. Baczkowski; Christian F. Doeller; Mona M. Garvert; Eric Schulz (NeurIPS, 2024)

Simplifying Latent Dynamics with Softly State-Invariant World Models. - Tankred Saanum; Peter Dayan; Eric Schulz (NeurIPS, 2024)

Predicting the Future with Simple World Models. - Tankred Saanum; Peter Dayan; Eric Schulz (CoRR, 2024)

Ecologically rational meta-learned inference explains human category learning. - Akshay K. Jagadish; Julian Coda-Forno; Mirko Thalmann; Eric Schulz; Marcel Binz (CoRR, 2024)

metabench - A Sparse Benchmark to Measure General Ability in Large Language Models. - Alexander Kipnis; Konstantinos Voudouris; Luca M. Schulze Buschoff; Eric Schulz (CoRR, 2024)

Next state prediction gives rise to entangled, yet compositional representations of objects. - Tankred Saanum; Luca M. Schulze Buschoff; Peter Dayan; Eric Schulz (CoRR, 2024)

Centaur: a foundation model of human cognition. - Marcel Binz; Elif Akata; Matthias Bethge; Franziska Brändle; Fred Callaway; Julian Coda-Forno; Peter Dayan; Can Demircan; Maria K. Eckstein; Noémi Élteto; Thomas L. Griffiths 001; Susanne Haridi; et al. (CoRR, 2024)

Sparse Autoencoders Reveal Temporal Difference Learning in Large Language Models. - Can Demircan; Tankred Saanum; Akshay Kumar Jagadish; Marcel Binz; Eric Schulz (ICLR, 2025)

metabench - A Sparse Benchmark of Reasoning and Knowledge in Large Language Models. - Alexander Kipnis; Konstantinos Voudouris; Luca M. Schulze Buschoff; Eric Schulz (ICLR, 2025)

Building, Reusing, and Generalizing Abstract Representations from Concrete Sequences. - Shuchen Wu; Mirko Thalmann; Peter Dayan; Zeynep Akata; Eric Schulz (ICLR, 2025)

Visual cognition in multimodal large language models. - Luca M. Schulze Buschoff; Elif Akata; Matthias Bethge; Eric Schulz (Nat. Mac. Intell., 2025)

Assessing and alleviating state anxiety in large language models. - Ziv Ben-Zion; Kristin Witte; Akshay K. Jagadish; Or Duek; Ilan Harpaz-Rotem; Marie-Christine Khorsandian; Achim Burrer; Erich Seifritz; Philipp Homan; Eric Schulz; Tobias Spiller (npj Digit. Medicine, 2025)

Towards Automation of Cognitive Modeling using Large Language Models. - Milena Rmus; Akshay K. Jagadish; Marvin Mathony; Tobias Ludwig 003; Eric Schulz (CoRR, 2025)

Discovering Chunks in Neural Embeddings for Interpretability. - Shuchen Wu; Stephan Alaniz; Eric Schulz; Zeynep Akata (CoRR, 2025)

Testing the limits of fine-tuning to improve reasoning in vision language models. - Luca M. Schulze Buschoff; Konstantinos Voudouris; Elif Akata; Matthias Bethge; Joshua B. Tenenbaum; Eric Schulz (CoRR, 2025)

Bringing Comparative Cognition To Computers. - Konstantinos Voudouris; Lucy G. Cheke; Eric Schulz (CoRR, 2025)

Concept-Guided Interpretability via Neural Chunking. - Shuchen Wu; Stephan Alaniz; Shyamgopal Karthik; Peter S. Dayan; Eric Schulz; Zeynep Akata (CoRR, 2025)

Automated scientific minimization of regret. - Marcel Binz; Akshay K. Jagadish; Milena Rmus; Eric Schulz (CoRR, 2025)

A foundation model to predict and capture human cognition. - Marcel Binz; Elif Akata; Matthias Bethge; Franziska Brändle; Fred Callaway; Julian Coda-Forno; Peter Dayan; Can Demircan; Maria K. Eckstein; Noémi Élteto; Thomas L. Griffiths 001; Susanne Haridi; et al. (Nat., 2025)