Human-level concept learning through probabilistic program induction

Cited by (1,005)

Items 701–800 of 1,005

1. Incremental Multi-Domain Learning with Network Latent Tensor Factorization
   Adrian Bulat, Jean Kossaifi, Georgios Tzimiropoulos, Maja Pantić · 2020 · AAAI Publications (The Association for the Advancement of Artificial Intelligence (AAAI))
2. Understanding exploration in humans and machines by formalizing the function of curiosity
   Rachit Dubey, Thomas L. Griffiths · 2020 · Current Opinion in Behavioral Sciences
3. BSNN: Towards faster and better conversion of artificial neural networks to spiking neural networks with bistable neurons
   Yang Li, Dongcheng Zhao, Yi Zeng · 2022 · Frontiers in Neuroscience
4. Mixing memory and desire: How memory reactivation supports deliberative decision‐making
   Shaoming Wang, Samuel Franklin Feng, Aaron M. Bornstein · 2021 · Wiley Interdisciplinary Reviews Cognitive Science
5. DocSynth: A Layout Guided Approach for Controllable Document Image Synthesis
   Sanket Biswas, Pau Riba, Josep Lladós, Umapada Pal · 2021 · Lecture notes in computer science
6. A fusion spatial attention approach for few-shot learning
   Heda Song, Bowen Deng, Michael P. Pound, Ender Özcan, Isaac Triguero A · 2021 · Information Fusion
7. PcGAN: A Noise Robust Conditional Generative Adversarial Network for One Shot Learning
   Lizhen Deng, Chunming He, Guoxia Xu, Hu Zhu, Hao Henry Wang · 2022 · IEEE Transactions on Intelligent Transportation Systems
8. Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object Interactions
   Huaizu Jiang, Xiaojian Ma, Weili Nie, Zhiding Yu, Yuke Zhu, Animashree Anandkumar · 2022 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
9. Azimuth-Aware Discriminative Representation Learning for Semi-Supervised Few-Shot SAR Vehicle Recognition
   Linbin Zhang, Xiangguang Leng, Sijia Feng, Xiaojie Ma, Kefeng Ji, Gangyao Kuang, Li Liu · 2023 · Remote Sensing
10. ESPT: A Self-Supervised Episodic Spatial Pretext Task for Improving Few-Shot Learning
    Yi Rong, Xiongbo Lu, Zhaoyang Sun, Yaxiong Chen, Shengwu Xiong · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
11. Amortized Variational Inference: A Systematic Review
    Ankush Ganguly, Sanjana Jain, Ukrit Watchareeruetai · 2023 · Journal of Artificial Intelligence Research
12. Few-shot learning in deep networks through global prototyping
    Sebastian Blaes, Thomas Burwick · 2017 · Neural Networks
13. Learning abstract visual concepts via probabilistic program induction in a Language of Thought
    Matthew C. Overlan, Robert A. Jacobs, Steven T. Piantadosi · 2017 · Cognition
14. People Infer Recursive Visual Concepts from Just a Few Examples
    Brenden M. Lake, Steven T. Piantadosi · 2019 · Computational Brain & Behavior
15. Probabilistic Autoencoder
    Vanessa Böhm, Uroš Seljak · 2020 · arXiv (Cornell University)
16. On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning
    Ren Wang, Kaidi Xu, Sijia Liu, Pin‐Yu Chen, Tsui-Wei Weng, Chuang Gan, Meng Wang · 2021 · arXiv (Cornell University)
17. MMT: Cross Domain Few-Shot Learning via Meta-Memory Transfer
    Wenjian Wang, Lijuan Duan, Yuxi Wang, Junsong Fan, Zhaoxiang Zhang · 2023 · IEEE Transactions on Pattern Analysis and Machine Intelligence
18. An image-driven machine learning approach to kinetic modeling of a discontinuous precipitation reaction
    Elizabeth J. Kautz, Wufei Ma, Saumyadeep Jana, Arun Devaraj, Vineet V. Joshi, Bülent Yener, D. Lewis · 2020 · Materials Characterization
19. The neural and cognitive architecture for learning from a small sample
    Aurelio Cortese, Benedetto De Martino, Mitsuo Kawato · 2019 · Current Opinion in Neurobiology
20. Neural network method for solving parabolic two-temperature microscale heat conduction in double-layered thin films exposed to ultrashort-pulsed lasers
    Aniruddha Bora, Weizhong Dai, Joshua P. Wilson, Jacob C. Boyt · 2021 · International Journal of Heat and Mass Transfer
21. Discrete and continuous representations and processing in deep learning: Looking forward
    Ruben Cartuyvels, Graham Spinks, Marie‐Francine Moens · 2021 · AI Open
22. Dataset Bias in Few-Shot Image Recognition
    Shuqiang Jiang, Yaohui Zhu, Chenlong Liu, Xinhang Song, Xiangyang Li, Weiqing Min · 2022 · IEEE Transactions on Pattern Analysis and Machine Intelligence
23. A conditional GAN-based approach for enhancing transfer learning performance in few-shot HCR tasks
    Nagwa Elaraby, Sherif Barakat, Amira Rezk · 2022 · Scientific Reports
24. Unsupervised Few-Shot Image Classification by Learning Features into Clustering Space
    Shuo Li, Fang Liu, Zehua Hao, Kaibo Zhao, Licheng Jiao · 2022 · Lecture notes in computer science
25. Two-way Concept-Cognitive Learning with Multi-source Fuzzy Context
    Xiaoyan Zhang, Doudou Guo, Weihua Xu · 2023 · Cognitive Computation
26. Few-shot learning for facial expression recognition: a comprehensive survey
    Chae-Lin Kim, Byung‐Gyu Kim · 2023 · Journal of Real-Time Image Processing
27. Detach and unite: A simple meta-transfer for few-shot learning
    Yaoyue Zheng, Xuetao Zhang, Zhiqiang Tian, Wei Zeng, Shaoyi Du · 2023 · Knowledge-Based Systems
28. Few-shot classification guided by generalization error bound
    Fan Liu, Sai Yang, Delong Chen, Huaxi Huang, Jun Wei Zhou · 2023 · Pattern Recognition
29. Few-Shot Learning
    Hugo Larochelle · 2020 · Springer eBooks
30. An Active Inference Approach to Modeling Structure Learning: Concept Learning as an Example Case
    Smith, R, Philipp Schwartenbeck, Thomas Parr, Karl John Friston · 2020 · UCL Discovery (University College London)
31. Convolution by Evolution: Differentiable Pattern Producing Networks
    Chrisantha Fernando, Dylan Banarse, Malcolm Reynolds, Frederic Besse, David Pfau, Max Jaderberg, Marc Lanctot, Daan Wierstra · 2016 · arXiv (Cornell University)
32. Fast Parametric Learning with Activation Memorization
    Jack W. Rae, Chris Dyer, Peter Dayan, Timothy Lillicrap · 2018 · arXiv (Cornell University)
33. Offline Meta-Reinforcement Learning with Advantage Weighting
    Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn · 2020 · arXiv (Cornell University)
34. Hierarchical VAEs Know What They Don't Know
    Jakob D. Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe · 2021 · arXiv (Cornell University)
35. Battery Prognostics and Health Management: AI and Big Data
    Di Li, Jin-Rui Nan, Andrew F. Burke, Jing-Yuan Zhao · 2024 · World Electric Vehicle Journal
36. Temporal Hallucinating for Action Recognition with Few Still Images
    Yali Wang, Lei Zhou, Yu Qiao · 2018 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
37. Image-Based Unknown Malware Classification with Few-Shot Learning Models
    Trung Kien Tran, Hiroshi Satō, Masao Kubo · 2019 · International Symposium on Computing and Networking Workshops (CANDARW)
38. Adaptation-Oriented Feature Projection for One-shot Action Recognition
    Yixiong Zou, Yemin Shi, Daochen Shi, Yaowei Wang, Yongsheng Liang, Yonghong Tian · 2020 · IEEE Transactions on Multimedia
39. A Few-shot Learning Approach for Historical Ciphered Manuscript Recognition
    Mohamed Ali Souibgui, Alícia Fornés, Yousri Kessentini, Crina Tudor · 2021 · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition
40. Few-shot image generation based on contrastive meta-learning generative adversarial network
    Aniwat Phaphuangwittayakul, Fangli Ying, Yi Guo, Liting Zhou, Nopasit Chakpitak · 2022 · The Visual Computer
41. CapCAM: A Multilevel Capacitive Content Addressable Memory for High-Accuracy and High-Scalability Search and Compute Applications
    Xiaoyang Ma, Hongtao Zhong, Nuo Xiu, Yiming Chen, Guodong Yin, Vijaykrishnan Narayanan, Yongpan Liu, Kai Ni, Huazhong Yang, Xueqing Li · 2022 · IEEE Transactions on Very Large Scale Integration (VLSI) Systems
42. Incremental Incomplete Concept-Cognitive Learning Model: A Stochastic Strategy
    Zhiming Liu, Jinhai Li, Xiao Zhang, Xizhao Wang · 2023 · IEEE Transactions on Neural Networks and Learning Systems
43. Incremental Generalized Category Discovery
    Bingchen Zhao, Oisin Mac Aodha · 2023 · IEEE/CVF International Conference on Computer Vision (ICCV)
44. Efficient Exploration in Constrained Environments with Goal-Oriented Reference Path
    Kei Ota, Yoko Sasaki, Devesh K. Jha, Yusuke Yoshiyasu, Asako Kanezaki · 2020 · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
45. Meta Networks.
    Tsendsuren Munkhdalai, Hong Qing Yu · 2017 · PubMed
46. Unsupervised Doodling and Painting with Improved SPIRAL
    John F. J. Mellor, Eunbyung Park, Yaroslav Ganin, I. Babuschkin, Tejas D. Kulkarni, Dan Rosenbaum, Andy Ballard, Théophane Weber, Oriol Vinyals, S. M. Ali Eslami · 2019 · arXiv (Cornell University)
47. Defining Benchmarks for Continual Few-Shot Learning
    Antreas Antoniou, Massimiliano Patacchiola, Mateusz Ochal, Amos Storkey · 2020 · arXiv (Cornell University)
48. Meta-Learning Symmetries by Reparameterization
    Allan Zhou, Tom Knowles, Chelsea Finn · 2020 · arXiv (Cornell University)
49. Deep Learning for Scene Classification: A Survey
    Delu Zeng, Minyu Liao, Mohammad Tavakolian, Yulan Guo, Bolei Zhou, Dewen Hu, Matti Pietikäinen, Li Liu · 2021 · arXiv (Cornell University)
50. Assessing Demand for Transparency in Intelligent Systems Using Machine Learning
    Vorm, Eric S. · 2018 · 2018 Innovations in Intelligent Systems and Applications (INISTA)
51. Rapidly adaptable automated interpretation of point-of-care COVID-19 diagnostics
    Siddarth Arumugam, Jiawei Ma, Uzay Macar, Guangxing Han, Kathrine McAulay, Darrell Ingram, Alexander Wang Ying, Harshit Harpaldas Chellani, Terry L. Chern, Kenta S. Reilly et al. · 2023 · Communications Medicine
52. Rethinking Few-Shot Class-Incremental Learning With Open-Set Hypothesis in Hyperbolic Geometry
    Yawen Cui, Zitong Yu, Wei Peng, Qi Tian, Li Liu · 2023 · IEEE Transactions on Multimedia
53. Semi-supervised symbol detection for piping and instrumentation drawings
    Mohit Gupta, Chialing Wei, Thomas Czerniawski · 2024 · Automation in Construction
54. Few-Shot Load Forecasting Under Data Scarcity in Smart Grids: A Meta-Learning Approach
    Georgios Tsoumplekas, Christos L. Athanasiadis, Dimitrios I. Doukas, Antonios C. Chrysopoulos, Pericles A. Mitkas · 2025 · Energies
55. Detection and estimation of mental fatigue in manual assembly process of complex products
    Hong Li Xiao, Yugang Duan, Zhongbo Zhang, Ming Li · 2017 · Assembly Automation
56. Behavior Is Everything: Towards Representing Concepts with Sensorimotor Contingencies
    Nicholas Hay, Michael M. Stark, Alexander A. Schlegel, Carter Wendelken, Dennis Park, Eric Purdy, Tom Silver, D. Scott Phoenix, Dileep George A · 2018 · Proceedings of the AAAI Conference on Artificial Intelligence
57. An exact penalty approach for optimization with nonnegative orthogonality constraints
    Bo Jiang, Xiang Meng, Zaiwen Wen, Xiaojun Chen · 2022 · Mathematical Programming
58. Feature hallucination via Maximum A Posteriori for few-shot learning
    Jiaying Wu, Ning Dong, Fan Liu, Sai Yang, Jinglu Hu · 2021 · Knowledge-Based Systems
59. What Can Knowledge Bring to Machine Learning?—A Survey of Low-shot Learning for Structured Data
    Yang Hu, Adriane P. Chapman, Guihua Wen, Dame Wendy Hall · 2022 · ACM Transactions on Intelligent Systems and Technology
60. StrokeStyles: Stroke-based Segmentation and Stylization of Fonts
    Daniel Berio, Frédéric Fol Leymarie, Paul Asente, Jose Echevarria · 2022 · ACM Transactions on Graphics
61. A review of emerging research directions in Abstract Visual Reasoning
    Mikołaj Małkiński, Jacek Mańdziuk · 2022 · Information Fusion
62. Learning by Seeing More Classes
    Fei Zhu, Xu-Yao Zhang, Rui-Qi Wang, Cheng-Lin Liu · 2022 · IEEE Transactions on Pattern Analysis and Machine Intelligence
63. An Eight-Core RISC-V Processor With Compute Near Last Level Cache in Intel 4 CMOS
    Gregory K. Chen, Phil C. Knag, Carlos Tokunaga, Ram Kumar Krishnamurthy · 2022 · IEEE Journal of Solid-State Circuits
64. AI Concepts for System of Systems Dynamic Interoperability
    Jacob Nilsson, Saleha Javed, Kim Albertsson, Jerker Delsing, Marcus Liwicki, Fredrik Sandin · 2024 · Sensors
65. Learning Multi-Way Relations via Tensor Decomposition With Neural Networks
    Koji Maruhashi, Masaru Todoriki, Takuya Ohwa, Keisuke Goto, Yu Hasegawa, Hiroya Inakoshi, Hirokazu Anai · 2018 · Proceedings of the AAAI Conference on Artificial Intelligence
66. Feature Learning for One-Shot Face Recognition
    Lingxiao Wang, Yali Li, Shengjin Wang · 2018 · Proceedings - International Conference on Image Processing
67. A Survey of Deep Learning Solutions for Multimedia Visual Content Analysis
    Muhammad Shahroz Nadeem, Virginia N. L. Franqueira, Xiaojun Zhai, Fatih Kurugöllü · 2019 · IEEE Access
68. Machine learning approaches for defect classification on aircraft fuselage images aquired by an UAV
    Julien Miranda, Jannic Veith, Stanislas Larnier, Ariane Herbulot, Michel Devy · 2019 · International Conference on Quality Control by Artificial Vision (QCAV)
69. Adaptive Learning Knowledge Networks for Few-Shot Learning
    Minghao Yan · 2019 · IEEE Access
70. Siamese Networks for Few-Shot Learning on Edge Embedded Devices
    Lungu, Iulia Alexandra, Aimar, Alessandro, Hu, Yuhuang, Delbruck, Tobi, Liu, Shih-Chii · 2020 · IEEE Journal on Emerging and Selected Topics in Circuits and Systems
71. Auto-Meta: Automated Gradient Based Meta Learner Search
    Jaehong Kim, Sangyeul Lee, Sungwan Kim, Moonsu Cha, Jung Kwon Lee, Youngduck Choi, Yong-Seok Choi, Cho, Dong-Yeon, Jiwon W. Kim · 2018 · arXiv (Cornell University)
72. Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning
    Weili Nie, Zhiding Yu, Lei Mao, Ankit Patel, Yuke Zhu, Animashree Anandkumar · 2020 · arXiv (Cornell University)
73. Sill-Net: Feature Augmentation with Separated Illumination Representation
    Haipeng Zhang, Zhong Liang Cao, Ziang Yan, Changshui Zhang · 2021 · arXiv (Cornell University)
74. The Quest for an Integrated Set of Neural Mechanisms Underlying Object Recognition in Primates
    Kohitij Kar, James J. DiCarlo · 2024 · Annual Review of Vision Science
75. Simple yet effective adaptive activation functions for physics-informed neural networks
    Jun Zhang, Chensen Ding · 2024 · Computer Physics Communications
76. A Comprehensive Review of Neuro-symbolic AI for Robustness, Uncertainty Quantification, and Intervenability
    Kamal Acharya, Houbing Song · 2025 · Arabian Journal for Science and Engineering
77. Diversity and Depth in Per-Example Routing Models
    Prajit Ramachandran, Quoc Viet Le · 2018 · International Conference on Learning Representations
78. Applying Probabilistic Programming to Affective Computing
    Desmond C. Ong, Harold Soh, Jamil Zaki, Noah D. Goodman · 2019 · IEEE Transactions on Affective Computing
79. Learning How to Generalize
    Joseph L. Austerweil, Sophia Sanborn, Thomas L. Griffiths · 2019 · Cognitive Science
80. Deep reinforcement one-shot learning for artificially intelligent classification in expert aided systems
    Anton Puzanov, Senyang Zhang, Kobi Cohen · 2020 · Engineering Applications of Artificial Intelligence
81. Oculomotor anticipation reveals a multitude of learning processes underlying the serial reaction time task
    Amir Tal, Ayala Bloch, Haggar Cohen-Dallal, Or Aviv, Simone Schwizer Ashkenazi, Moshe Bar, Eli Vakil · 2021 · Scientific Reports
82. A theory of relation learning and cross-domain generalization.
    Leonidas A. A. Doumas, Guillermo Puebla, Andrea E. Martin, John E. Hummel · 2022 · Psychological Review
83. Hyperspectral Estimation of Soil Copper Concentration Based on Improved TabNet Model in the Eastern Junggar Coalfield
    Yuan Wang, Abdugheni Abliz, Hongbing Ma, Li Liu, Alishir Kurban, Ümüt Halik, Matti Pietikäinen, Wenjuan Wang · 2022 · IEEE Transactions on Geoscience and Remote Sensing
84. Computational Modeling of Bilingual Language Learning: Current Models and Future Directions
    Ping Li, Qihui Xu · 2022 · Language Learning
85. Combining Model-Agnostic Meta-Learning and Transfer Learning for Regression
    Wahyu Fadli Satrya, Ji-Hoon Yun · 2023 · Sensors
86. Co-Domain Embedding Using Deep Quadruplet Networks for Unseen Traffic Sign Recognition
    Junsik Kim, Seokju Lee, Tae-Hyun Oh, In So Kweon · 2018 · Proceedings of the AAAI Conference on Artificial Intelligence
87. Inverting The Generator Of A Generative Adversarial Network (II)
    Antonia Creswell, Anil Anthony Bharath · 2018 · arXiv (Cornell University)
88. The Kanerva Machine: A Generative Distributed Memory
    Yan Xiang Wu, Greg Wayne, Alex Graves, Timothy Lillicrap · 2018 · arXiv (Cornell University)
89. Diverse Few-Shot Text Classification with Multiple Metrics
    Mo Yu, Xiaoxiao Guo, Jinfeng Yi, Shiyu Chang, Saloni Potdar, Yu Cheng, Gerald J. Tesauro, Haoyu Wang, Bowen Zhou · 2018 · arXiv (Cornell University)
90. Metalearning with Hebbian Fast Weights
    Tsendsuren Munkhdalai, Adam Trischler · 2018 · arXiv (Cornell University)
91. Penalty Method for Inversion-Free Deep Bilevel Optimization
    Akshay Mehra, Jihun Hamm · 2019 · arXiv (Cornell University)
92. Meta-Learning Deep Energy-Based Memory Models
    Sergey Bartunov, Jack W. Rae, Simon Osindero, Timothy Lillicrap · 2019 · arXiv (Cornell University)
93. Sampling for Bayesian Program Learning
    Kevin Ellis, Armando Solar-Lezama, Joshua B. Tenenbaum · 2016 · DSpace@MIT (Massachusetts Institute of Technology)
94. New insights into olivo-cerebellar circuits for learning from a small training sample
    Isao T. Tokuda, Huu Hoang, Mitsuo Kawato · 2017 · Current Opinion in Neurobiology
95. Putting a bug in ML: The moth olfactory network learns to read MNIST
    Charles B. Delahunt, J. Nathan Kutz · 2019 · Neural Networks
96. Safe Artificial General Intelligence via Distributed Ledger Technology
    Kristen W. Carlson · 2019 · Big Data and Cognitive Computing
97. Recent Trends in Context Exploitation for Information Fusion and AI
    Lauro Snidaro, Jesús Garcı́a, James Llinas, Erik Blasch · 2019 · AI Magazine
98. Improving Siamese Networks for One-Shot Learning Using Kernel-Based Activation Functions
    Shruti Jadon, Aditya Arcot Srinivasan · 2020 · Advances in intelligent systems and computing
99. Machine Number Sense: A Dataset of Visual Arithmetic Problems for Abstract and Relational Reasoning
    Wenhe Zhang, Chi Zhang, Yixin Zhu, Song Chun Zhu · 2020 · Proceedings of the AAAI Conference on Artificial Intelligence
100. The Change of Judicial Power in China in the Era of Artificial Intelligence
     Weidong Ji · 2020 · Asian Journal of Law and Society