ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2006.08381
  4. Cited By
DreamCoder: Growing generalizable, interpretable knowledge with
  wake-sleep Bayesian program learning

DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning

15 June 2020
Kevin Ellis
Catherine Wong
Maxwell Nye
Mathias Sablé-Meyer
Luc Cary
Lucas Morales
Luke B. Hewitt
Armando Solar-Lezama
J. Tenenbaum
    NAI
    CLL
ArXivPDFHTML

Papers citing "DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning"

34 / 34 papers shown
Title
LLM-Guided Probabilistic Program Induction for POMDP Model Estimation
LLM-Guided Probabilistic Program Induction for POMDP Model Estimation
Aidan Curtis
Hao Tang
Thiago Veloso
Kevin Ellis
Joshua B. Tenenbaum
Tomás Lozano-Pérez
Leslie Pack Kaelbling
74
0
0
04 May 2025
TurtleBench: A Visual Programming Benchmark in Turtle Geometry
TurtleBench: A Visual Programming Benchmark in Turtle Geometry
Sina Rismanchian
Yasaman Razeghi
Sameer Singh
Shayan Doroudi
49
1
0
31 Oct 2024
A Complexity-Based Theory of Compositionality
A Complexity-Based Theory of Compositionality
Eric Elmoznino
Thomas Jiralerspong
Yoshua Bengio
Guillaume Lajoie
CoGe
61
4
0
18 Oct 2024
COOL: Efficient and Reliable Chain-Oriented Objective Logic with Neural Networks Feedback Control for Program Synthesis
COOL: Efficient and Reliable Chain-Oriented Objective Logic with Neural Networks Feedback Control for Program Synthesis
Jipeng Han
39
0
0
02 Oct 2024
Intelligence Analysis of Language Models
Intelligence Analysis of Language Models
Liane Galanti
Ethan Baron
LRM
37
1
0
20 Jul 2024
LGR2: Language Guided Reward Relabeling for Accelerating Hierarchical Reinforcement Learning
LGR2: Language Guided Reward Relabeling for Accelerating Hierarchical Reinforcement Learning
Utsav Singh
Pramit Bhattacharyya
Vinay P. Namboodiri
LM&Ro
47
1
0
09 Jun 2024
Neural Slot Interpreters: Grounding Object Semantics in Emergent Slot Representations
Neural Slot Interpreters: Grounding Object Semantics in Emergent Slot Representations
Bhishma Dedhia
N. Jha
OCL
51
1
0
02 Feb 2024
Learning a Hierarchical Planner from Humans in Multiple Generations
Learning a Hierarchical Planner from Humans in Multiple Generations
Leonardo Hernandez Cano
Yewen Pu
Robert D. Hawkins
Josh Tenenbaum
Armando Solar-Lezama
26
2
0
17 Oct 2023
LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and
  the Importance of Object-based Representations
LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations
Yudong Xu
Wenhao Li
Pashootan Vaezipoor
Scott Sanner
Elias Boutros Khalil
LRM
28
54
0
26 May 2023
Neural Machine Translation for Code Generation
Neural Machine Translation for Code Generation
K. Dharma
Clayton T. Morrison
32
4
0
22 May 2023
On the Complexity of Bayesian Generalization
On the Complexity of Bayesian Generalization
Yuge Shi
Manjie Xu
J. Hopcroft
Kun He
J. Tenenbaum
Song-Chun Zhu
Ying Nian Wu
Wenjuan Han
Yixin Zhu
28
4
0
20 Nov 2022
ObSynth: An Interactive Synthesis System for Generating Object Models
  from Natural Language Specifications
ObSynth: An Interactive Synthesis System for Generating Object Models from Natural Language Specifications
Alex Gu
Tamara Mitrovska
D. Vélez
Jacob Andreas
Armando Solar-Lezama
SyDa
25
1
0
20 Oct 2022
Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus
Graphs, Constraints, and Search for the Abstraction and Reasoning Corpus
Yudong Xu
Elias Boutros Khalil
Scott Sanner
GNN
16
29
0
18 Oct 2022
Towards biologically plausible Dreaming and Planning in recurrent
  spiking networks
Towards biologically plausible Dreaming and Planning in recurrent spiking networks
C. Capone
P. Paolucci
CLL
28
7
0
20 May 2022
Structured, flexible, and robust: benchmarking and improving large
  language models towards more human-like behavior in out-of-distribution
  reasoning tasks
Structured, flexible, and robust: benchmarking and improving large language models towards more human-like behavior in out-of-distribution reasoning tasks
K. M. Collins
Catherine Wong
Jiahai Feng
Megan Wei
J. Tenenbaum
LRM
22
57
0
11 May 2022
Identifying concept libraries from language about object structure
Identifying concept libraries from language about object structure
Catherine Wong
William P. McCarthy
Gabriel Grand
Yoni Friedman
J. Tenenbaum
Jacob Andreas
Robert D. Hawkins
Judith E. Fan
OCL
26
13
0
11 May 2022
From {Solution Synthesis} to {Student Attempt Synthesis} for Block-Based
  Visual Programming Tasks
From {Solution Synthesis} to {Student Attempt Synthesis} for Block-Based Visual Programming Tasks
Adish Singla
Nikitas Theodoropoulos
28
13
0
03 May 2022
Compositional Generalization and Decomposition in Neural Program
  Synthesis
Compositional Generalization and Decomposition in Neural Program Synthesis
Kensen Shi
Joey Hong
Manzil Zaheer
Pengcheng Yin
Charles Sutton
37
5
0
07 Apr 2022
Abstraction for Deep Reinforcement Learning
Abstraction for Deep Reinforcement Learning
Murray Shanahan
Melanie Mitchell
OffRL
27
28
0
10 Feb 2022
Explanatory Learning: Beyond Empiricism in Neural Networks
Explanatory Learning: Beyond Empiricism in Neural Networks
Antonio Norelli
Giorgio Mariani
Luca Moschella
Andrea Santilli
Giambattista Parascandolo
Simone Melzi
Emanuele Rodolà
14
2
0
25 Jan 2022
Automated causal inference in application to randomized controlled
  clinical trials
Automated causal inference in application to randomized controlled clinical trials
Ji Q. Wu
N. Horeweg
M. de Bruyn
R. Nout
I. Jürgenliemk-Schulz
...
H. Nijman
V. Smit
T. Bosse
C. Creutzberg
V. Koelzer
CML
24
14
0
15 Jan 2022
Noether Networks: Meta-Learning Useful Conserved Quantities
Noether Networks: Meta-Learning Useful Conserved Quantities
Ferran Alet
Dylan D. Doblar
Allan Zhou
J. Tenenbaum
Kenji Kawaguchi
Chelsea Finn
73
26
0
06 Dec 2021
ReaSCAN: Compositional Reasoning in Language Grounding
ReaSCAN: Compositional Reasoning in Language Grounding
Zhengxuan Wu
Elisa Kreiss
Desmond C. Ong
Christopher Potts
CoGe
LRM
29
22
0
18 Sep 2021
Procedures as Programs: Hierarchical Control of Situated Agents through
  Natural Language
Procedures as Programs: Hierarchical Control of Situated Agents through Natural Language
Shuyan Zhou
Pengcheng Yin
Graham Neubig
LM&Ro
14
1
0
16 Sep 2021
Learning to Synthesize Programs as Interpretable and Generalizable
  Policies
Learning to Synthesize Programs as Interpretable and Generalizable Policies
Dweep Trivedi
Jesse Zhang
Shao-Hua Sun
Joseph J. Lim
NAI
24
72
0
31 Aug 2021
A Review of Some Techniques for Inclusion of Domain-Knowledge into Deep
  Neural Networks
A Review of Some Techniques for Inclusion of Domain-Knowledge into Deep Neural Networks
T. Dash
Sharad Chitlangia
Aditya Ahuja
A. Srinivasan
30
128
0
21 Jul 2021
Improving Coherence and Consistency in Neural Sequence Models with
  Dual-System, Neuro-Symbolic Reasoning
Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoning
Maxwell Nye
Michael Henry Tessler
J. Tenenbaum
Brenden Lake
33
117
0
06 Jul 2021
Leveraging Language to Learn Program Abstractions and Search Heuristics
Leveraging Language to Learn Program Abstractions and Search Heuristics
Catherine Wong
Kevin Ellis
J. Tenenbaum
Jacob Andreas
24
54
0
18 Jun 2021
Communicating Natural Programs to Humans and Machines
Communicating Natural Programs to Humans and Machines
Samuel Acquaviva
Yewen Pu
Marta Kryven
Theo Sechopoulos
Catherine Wong
Gabrielle Ecanow
Maxwell Nye
Michael Henry Tessler
J. Tenenbaum
30
40
0
15 Jun 2021
Engineering Sketch Generation for Computer-Aided Design
Engineering Sketch Generation for Computer-Aided Design
Karl D. D. Willis
P. Jayaraman
Joseph G. Lambourne
Hang Chu
Yewen Pu
3DV
113
61
0
19 Apr 2021
Inferring CAD Modeling Sequences Using Zone Graphs
Inferring CAD Modeling Sequences Using Zone Graphs
Xianghao Xu
Wenzhe Peng
Chin-Yi Cheng
Karl D. D. Willis
Daniel E. Ritchie
3DPC
AI4CE
25
65
0
30 Mar 2021
PLAD: Learning to Infer Shape Programs with Pseudo-Labels and
  Approximate Distributions
PLAD: Learning to Infer Shape Programs with Pseudo-Labels and Approximate Distributions
R. K. Jones
Homer Walke
Daniel E. Ritchie
25
24
0
25 Nov 2020
Making sense of sensory input
Making sense of sensory input
Maciej Wołczyk
Jacek Tabor
Johannes Welbl
Szymon Maszke
Marek Sergot
19
52
0
05 Oct 2019
Building machines that adapt and compute like brains
Building machines that adapt and compute like brains
Brenden Lake
J. Tenenbaum
AI4CE
FedML
NAI
AILaw
254
890
0
11 Nov 2017
1