Theory
1,949 items in 14 lists
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PAL: Program-aided Language Models proceedings.mlr.press
ICML'23, 2023. [All Versions]. Paper presenting an approach that uses the LLM to read natural language problems and generate programs as the intermediate reasoning steps, but offloads the solution step to a runtime such as a Python interpreter. With PAL, decomposing the natural…
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A Language for Counterfactual Generative Models proceedings.mlr.press
ICML'21, 2021. [All Versions]. [Project]. This paper presents Omega, a probabilistic programming language with support for counterfactual inference. This feature is accomplished by introducing a new operator to probabilistic programming akin to Pearl’s do.
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AGENT: A Benchmark for Core Psychological Reasoning proceedings.mlr.press
ICML'21, 2021. [All Versions]. Inspired by cognitive development studies on intuitive psychology, this paper presents a benchmark consisting of a large dataset of procedurally generated 3D animations, AGENT (Action, Goal, Efficiency, coNstraint, uTility), structured around four…
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TeachMyAgent: a Benchmark for Automatic Curriculum Learning in Deep RL proceedings.mlr.press
ICML'21, 2021. [All Versions]. [Project].
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Inverse Constrained Reinforcement Learning proceedings.mlr.press
ICML'21, 2021. [All Versions].
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SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning proceedings.mlr.press
ICML'21, 2021. [All Versions]. [Code].
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Latent Programmer: Discrete Latent Codes for Program Synthesis proceedings.mlr.press
ICML'21, 2021. [All Versions]. Paper introducing the Latent Programmer, a two-level program synthesis method that first predicts a discrete latent code from input/output examples, and then generates the program in the target language.
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PClean: Bayesian Data Cleaning at Scale with Domain-Specific Probabilistic Programming proceedings.mlr.press
ICML'21, 2021. [All Versions]. This work presents PClean, a probabilistic programming language (PPL) for leveraging dataset-specific knowledge to automate Bayesian cleaning, automating Bayesian approaches given the diversity of real-world error patterns and the hardness of…
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Latent Space Factorisation and Manipulation via Matrix Subspace Projection proceedings.mlr.press
ICML'20, 2020. [All Versions].
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Functional neuroanatomy of intuitive physical inference pnas.org
Proceedings of the National Academy of Sciences, 2016. [All Versions]. A piece of evidence for the functional part of intuitive physics in human brain.
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Bayesian modeling of human–AI complementarity pnas.org
Proceedings of the National Academy of Sciences, 2022. [All Versions]. A Bayesian framework for combining the predictions and different types of confidence scores from humans and machines.
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Proceedings of the National Academy of Sciences, 2021. [All Versions].
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Finding scientific topics pnas.org
Proceedings of the National Academy of Sciences, 2004. [All Versions]. A first step in identifying the content of a document is determining which topics that document addresses. This paper describes a generative model for documents, in which each document is generated by…
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Slowed Canonical Progress in Large Fields of Science pnas.org
Proceedings of the National Academy of Sciences, 2021. [All Verisions]. An analysis of why too many papers published each year in a field can lead to stagnation rather than advance.
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Scaling up psychology via Scientific Regret Minimization pnas.org
Proceedings of the National Academy of Sciences, 2020. [All Versions]. The statistical and ecological basis for scaling up behavioral studies.
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Meta-assessment of Bias in Science pnas.org
Proceedings of the National Academy of Sciences, 2017. [All Verisions]. An analysis of bias patterns and risk factors in science.
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Understanding the role of Individual Units in a Deep Neural Network pnas.org
Proceedings of the National Academy of Sciences, 2020. [All Versions]. David Bau's review on network dissection for discriminative and generative models.
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Rapid trail-and-error learning with simulation supports flexible tool use and physical reasoning. pnas.org
Proceedings of the National Academy of Sciences, 2020. [All Versions]. [Project]. [Appendix]. Many animals, and an increasing number of artificial agents, display sophisticated capabilities to perceive and manipulate objects. But human beings remain distinctive in their…
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Unsupervised learning by competing hidden units pnas.org
Proceedings of the National Academy of Sciences, 2019. [All Versions].
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Emergence of analogy from relation learning pnas.org
Proceedings of the National Academy of Sciences, 2019. [All Versions]. Analogy feature in language models.
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Simulation as an engine of physical scene understanding pnas.org
Proceedings of the National Academy of Sciences, 2013. [All Versions]. [Appendix]. The first attempt to computationally simulate intuitive physics.
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Communicating artificial neural networks develop efficient color-naming systems pnas.org
Proceedings of the National Academy of Sciences, 2021. [All Versions]. Simulating the emergence of code as the communication bottleneck in color learning task.
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Computational evidence for hierarchically structured reinforcement learning in humans pnas.org
Proceedings of the National Academy of Sciences, 2020. [All Versions]. A piece of evidence on hierarchical human planning.
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The logic of universalization guides moral judgment pnas.org
Proceedings of the National Academy of Sciences, 2020. [All Versions].
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Origins of the concepts cause, cost, and goal in prereaching infants pnas.org
Proceedings of the National Academy of Sciences, 2019. [All Versions].
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Evidence integration in model-based tree search pnas.org
Proceedings of the National Academy of Sciences, 2015. [All Versions].
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Kinematic mental simulations in abduction and deduction pnas.org
Proceedings of the National Academy of Sciences, 2013. [All Versions]. This paper presents a theory, and its computer implementation, of how mental simulations underlie the abductions of informal algorithms and deductions from these algorithms. Three experiments tested the…
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Insightful problem solving and creative tool modification by captive nontool-using rooks pnas.org
Proceedings of the National Academy of Sciences, 2009. [All Versions]. [Supplementary Material]. A piece of evidence on creative tool use in intelligent animals.
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Supervenience plato.stanford.edu
Plato Stanford. A computational philosophy account on supervenience, where a set of properties A supervenes upon another set B just in case no two things can differ with respect to A-properties without also differing with respect to their B-properties.
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Sense-Data plato.stanford.edu
Plato Stanford.
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Self-Knowledge plato.stanford.edu
Plato Stanford. A computational philosophy account on self-knowledge, which standardly refers to knowledge of one's own mental states—that is, of what one is feeling or thinking, or what one believes or desires.
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Scientific Representation plato.stanford.edu
Plato Stanford. A computational philosophy account on scientific representation, focusing on how scientific models represent their target systems.
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Scientific Reduction plato.stanford.edu
Plato Stanford. A computational philosophy account on Scientific Reduction, which comes with no explicit boundary with Explanation.
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Scientific Explanation plato.stanford.edu
Plato Stanford. A computational philosophy account on Scientific Explanation, a canonical application of Abduction.
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Scientific Discovery plato.stanford.edu
Plato Stanford. A computational philosophy account on Scientific Discovery, the process or product of successful scientific inquiry, sometimes an Abduction-like (Explanation) thinking pattern.
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Analogy and Analogical Reasoning plato.stanford.edu
Plato Stanford. A computational philosophy account on Analogy, a comparison between two objects, or systems of objects, that highlights respects in which they are thought to be similar.
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Instrumental Rationality plato.stanford.edu
Plato Stanford. A computational philosophy account on Instrumental Rationality, a dabate on whether an agent's decision is made intentionally or out of rational coherence.
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Pragmatics plato.stanford.edu
Plato Stanford. A computational philosophy account of Pragmatics, whilch studies utterances in specific contexts.
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First-order Model Theory plato.stanford.edu
Plato Stanford. A computational philosophy account on First-order Model Theory, which is a branch of mathematics that deals with the relationships between descriptions in first-order languages and the structures that satisfy these descriptions.
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Metaphor plato.stanford.edu
Plato Stanford. A computational philosophy account on Metaphor, a poetically or rhetorically ambitious use of words, a figurative as opposed to literal use.
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Mental Imagery plato.stanford.edu
Plato Stanford.
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Logic Pluralism plato.stanford.edu
Plato Stanford. A computational philosophy account on Logic Pluralism, which is the view that there is more than one correct logic.
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Logical Consequence plato.stanford.edu
Plato Stanford. A computational philosophy account on Logical Consequence, which is about the relation between premises and conclusions in valid arguments.
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Temporal Logic plato.stanford.edu
Plato Stanford.
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Paraconsistent Logic plato.stanford.edu
Plato Stanford. A computational philosophy account on Paraconsistent Logic, where any logic is paraconsistent as long as it is not explosive.
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Logic and Ontology plato.stanford.edu
Plato Stanford. A computational philosophy account on logic and ontology, mainly about the intersections of logic and ontology in many significant philosophy problems.
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Non-monotonic Logic plato.stanford.edu
Plato Stanford. A computational philosophy account on Non-monotonic Logic, a family of formal frameworks devised to capture and represent defeasible inference.
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Modal Logic plato.stanford.edu
Plato Stanford. A computational philosophy account on Modal Logic, which is the study of the deductive behavior of the expressions 'it is necessary that' and 'it is possible that'.
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Inductive Logic plato.stanford.edu
Plato Stanford. A computational philosophy account on Inductive Logic, which is a logic of evidential support.
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Second-order and Higher-order Logic plato.stanford.edu
Plato Stanford.
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