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2020 – today
- 2024
[c38]Bonan Zhao, Christopher G. Lucas, Neil R. Bramley:
Constructing Deep Concepts through Shallow Search. AAAI Spring Symposia 2024: 600-602- 2023
- [c37]Victor Btesh, David A. Lagnado, Maarten Speekenbrink, Neil R. Bramley:
Swipe and hold: composing interventions in continuous time causal learning. CogSci 2023 - [c36]Samuel J. Cheyette, Frederick Callaway, Neil R. Bramley, Jonathan D. Nelson, Josh Tenenbaum:
People seek easily interpretable information. CogSci 2023 - [c35]Stephanie Droop, Neil R. Bramley:
Extending counterfactual reasoning models to unconstrained social explanations. CogSci 2023 - [c34]Tadeg Quillien, Aba Szollosi, Neil R. Bramley, Chris Lucas:
Causal inference shapes counterfactual plausibility. CogSci 2023 - [c33]Aba Szollosi, Vlad Grigoras, Tadeg Quillien, Chris Lucas, Neil R. Bramley:
How do instructions, examples, and testing shape task representations? CogSci 2023 - [i4]Simon Valentin, Steven Kleinegesse, Neil R. Bramley, Peggy Seriès, Michael U. Gutmann, Christopher G. Lucas:
Designing Optimal Behavioral Experiments Using Machine Learning. CoRR abs/2305.07721 (2023) - 2022
- [j1]Bob Rehder, Zachary J. Davis, Neil Bramley
:
The Paradox of Time in Dynamic Causal Systems. Entropy 24(7): 863 (2022) - [c32]Stephanie Droop, Neil R. Bramley:
Inferring epistemic intention in simulated physical microworlds. CogSci 2022 - [c31]Tianwei Gong, Neil R. Bramley:
Intuitions and Perceptual Constraints on Causal Learning from Dynamics. CogSci 2022 - [c30]Nicolas Marchant, Bonan Zhao, Neil R. Bramley, Diego Morales, Sergio E. Chaigneau:
Categorizing perceived causal events. CogSci 2022 - [c29]Aba Szollosi, Neil R. Bramley:
Generating and evaluating hypothesis testing strategies. CogSci 2022 - [c28]Bonan Zhao, Neil R. Bramley, Chris Lucas:
Powering up causal generalization: A model of human conceptual bootstrapping with adaptor grammars. CogSci 2022 - 2021
- [c27]Jan-Philipp Fränken, Simon Valentin, Chris Lucas, Neil R. Bramley:
Know your network: Sensitivity to structure in social learning. CogSci 2021 - [c26]Simon Valentin, Steven Kleinegesse, Neil R. Bramley, Michael U. Gutmann, Chris Lucas:
Bayesian Experimental Design for Intractable Models of Cognition. CogSci 2021 - [c25]Simon Valentin, Bonan Zhao, Chentian Jiang, Neil Bramley, Chris Lucas:
Symbolic and Sub-Symbolic Systems in People and Machines. CogSci 2021 - [i3]Simon Valentin, Steven Kleinegesse, Neil R. Bramley, Michael U. Gutmann, Christopher G. Lucas:
Bayesian Optimal Experimental Design for Simulator Models of Cognition. CoRR abs/2110.15632 (2021) - [i2]Bonan Zhao, Christopher G. Lucas, Neil R. Bramley:
Building Object-based Causal Programs for Human-like Generalization. CoRR abs/2111.12560 (2021) - 2020
- [c24]Zachary Davis, Neil Bramley, Bob Rehder:
The Paradox of Time in Dynamic Causal Systems. CogSci 2020 - [c23]Zachary Davis, Neil Bramley, Bob Rehder, Todd M. Gureckis:
Dynamic Control Under Changing Goals. CogSci 2020 - [c22]Jan-Philipp Fränken, Nikolas Theodoropoulos, Adam Moore, Neil Bramley:
Belief revision in a micro-social network: Modeling sensitivity to statistical dependencies in social learning. CogSci 2020 - [c21]Tianwei Gong, Neil Bramley:
What you didn't see: Prevention and generation in continuous time causal induction. CogSci 2020 - [c20]Ethan Ludwin-Peery, Neil Bramley, Ernest Davis, Todd M. Gureckis:
A Generalization Test of Conjunction Errors in Physical Reasoning. CogSci 2020 - [c19]Héctor Otero Mediero, Neil Bramley:
Contrasting RNN-based and simulation-based models of human physical parameter inference. CogSci 2020 - [c18]Simon Valentin, Neil Bramley, Christopher Lucas:
Learning Hidden Causal Structure from Temporal Data. CogSci 2020 - [c17]Bonan Zhao, Neil Bramley:
Order Effects in One-shot Causal Generalization. CogSci 2020
2010 – 2019
- 2019
- [c16]Ethan Ludwin-Peery, Neil Bramley, Ernest Davis, Todd M. Gureckis:
Limits on the Use of Simulation in Physical Reasoning. CogSci 2019: 707-713 - [c15]Shuaiji Li, Yu Sun, Sijia Liu, Tianyu Wang, Todd M. Gureckis, Neil Bramley:
Active physical inference via reinforcement learning. CogSci 2019: 2126-2132 - [c14]Zhiwei Li, Neil Bramley, Todd M. Gureckis:
The critical moment is coming: Modeling the dynamics of suspense. CogSci 2019: 2133-2139 - 2018
- [c13]Neil Bramley, Anselm Rothe, Josh Tenenbaum, Fei Xu, Todd M. Gureckis:
Grounding Compositional Hypothesis Generation in Specific Instances. CogSci 2018 - [c12]Neil Bramley, Eric Schulz, Fei Xu, Josh Tenenbaum:
Learning as program induction. CogSci 2018 - [c11]Zachary Davis, Neil Bramley, Bob Rehder:
Causal Structure Learning with Continuous Variables in Continuous Time. CogSci 2018 - [c10]Zachary Davis, Neil Bramley, Bob Rehder, Todd M. Gureckis:
A Causal Model Approach to Dynamic Control. CogSci 2018 - [c9]Zhiwei Li, Neil Bramley, Todd M. Gureckis:
Modeling dynamics of suspense and surprise. CogSci 2018 - [c8]Yuan Meng, Neil Bramley, Fei Xu:
Children's Causal Interventions Combine Discrimination and Confirmation. CogSci 2018 - 2017
- [c7]Neil Bramley, Ralf Mayrhofer, Tobias Gerstenberg, David A. Lagnado:
Causal learning from interventions and dynamics in continuous time. CogSci 2017 - [c6]Anna Coenen, Neil Bramley, Azzurra Ruggeri, Todd M. Gureckis:
Beliefs about sparsity affect causal experimentation. CogSci 2017 - [c5]Eric Schulz, Edgar D. Klenske, Neil Bramley, Maarten Speekenbrink:
Strategic exploration in human adaptive control. CogSci 2017 - 2016
- [c4]Neil Bramley, Tobias Gerstenberg, Joshua B. Tenenbaum:
Natural science: Active learning in dynamic physical microworlds. CogSci 2016 - [i1]Neil R. Bramley, Peter Dayan, Thomas L. Griffiths, David A. Lagnado:
Formalizing Neurath's Ship: Approximate Algorithms for Online Causal Learning. CoRR abs/1609.04212 (2016) - 2015
- [c3]Neil Bramley, Peter Dayan, David A. Lagnado:
Staying afloat on Neurath's boat - Heuristics for sequential causal learning. CogSci 2015 - 2014
- [c2]Neil Bramley, Tobias Gerstenberg, David A. Lagnado:
The order of things: Inferring causal structure from temporal patterns. CogSci 2014 - 2013
- [c1]Neil Bramley, David A. Lagnado, Maarten Speekenbrink:
Mechanisms of Active Causal Learning. CogSci 2013
Coauthor Index
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last updated on 2024-06-04 20:45 CEST by the dblp team
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