International Conference on Neurosymbolic Learning and Reasoning
NeSy
C
CORE rank
CORE rank (raw)
C
Fields of research
Artificial Intelligence · Machine Learning · Theory of Computation
Papers indexed
250
2008–2025
Papers per year
200858 peak2025
Most published authors
NeSy papers
250 records sourced from DBLP. Search titles, filter by year, sort by recency.
| Year | Title | Authors |
|---|---|---|
| 2023 | Interpretable Neural-Symbolic Concept Reasoning. | Pietro Barbiero, Gabriele Ciravegna, Francesco Giannini, Mateo Espinosa Zarlenga, Lucie Charlotte Magister, Alberto Tonda, Pietro Li, Frdric Precioso, Mateja Jamnik, Giuseppe Marra |
| 2023 | Learning Logic Constraints From Demonstration. | Mattijs Baert, Sam Leroux, Pieter Simoens |
| 2023 | Verifying Strategic Abilities of Neural-Symbolic Multi-agent Systems. | Michael Akintunde, Elena Botoeva, Panagiotis Kouvaros, Alessio Lomuscio |
| 2023 | Semantic Probabilistic Layers for Neuro-Symbolic Learning. | Kareem Ahmed, Stefano Teso, Kai-Wei Chang, Guy Van den Broeck, Antonio Vergari |
| 2022 | Grounding LTLf Specifications in Images. | Elena Umili, Roberto Capobianco, Giuseppe De Giacomo |
| 2022 | Neural Analogical Reasoning. | Atharv Sonwane, Abhinav Lalwani, Sweta Mahajan, Gautam Shroff, Lovekesh Vig |
| 2022 | Knowledge-based Analogical Reasoning in Neuro-symbolic Latent Spaces. | Vishwa Shah, Aditya Sharma, Gautam Shroff, Lovekesh Vig, Tirtharaj Dash, Ashwin Srinivasan |
| 2022 | Propositional Reasoning via Neural Transformer Language Models. | Oscar J. Romero, Anthony Tomasic, Aaron Steinfeld, John Zimmerman |
| 2022 | From Subsymbolic to Symbolic: A Blueprint for Investigation. | Joseph Pober, Michael Luck, Odinaldo Rodrigues |
| 2022 | Modular Design Patterns for Neural-symbolic Integration: Refinement and Combination. | Till Mossakowski |
| 2022 | Learning Proof Path Selection Policies in Neural Theorem Proving. | Matthew Morris, Pasquale Minervini, Phil Blunsom |
| 2022 | CLEVR-Math: A Dataset for Compositional Language, Visual and Mathematical Reasoning. | Adam Dahlgren Lindstrm, Savitha Sam Abraham |
| 2022 | Differentiable Rule Induction with Learned Relational Features. | Remy Kusters, Yusik Kim, Marine Collery, Christian de Sainte Marie, Shubham Gupta |
| 2022 | ESC-Rules: Explainable, Semantically Constrained Rule Sets. | Martin Glauer, Robert West, Susan Michie, Janna Hastings |
| 2022 | Combining Fast and Slow Thinking for Human-like and Efficient Decisions in Constrained Environments. | Marianna Bergamaschi Ganapini, Murray Campbell, Francesco Fabiano, Lior Horesh, Jonathan Lenchner, Andrea Loreggia, Nicholas Mattei, Francesca Rossi, Biplav Srivastava, K. Brent Venable |
| 2022 | Towards Educating Artificial Neural Systems. | Simon Colton |
| 2022 | Logic Tensor Networks for Top-N Recommendation. | Tommaso Carraro, Alessandro Daniele, Fabio Aiolli, Luciano Serafini |
| 2022 | Multi-Step Deductive Reasoning Over Natural Language: An Empirical Study on Out-of-Distribution Generalisation. | Qiming Bao, Alex Yuxuan Peng, Tim Hartill, Neset Tan, Zhenyun Deng, Michael Witbrock, Jiamou Liu |
| 2022 | Visual Sudoku Puzzle Classification: A Suite of Collective Neuro-Symbolic Tasks. | Eriq Augustine, Connor Pryor, Charles Dickens, Jay Pujara, William Yang Wang, Lise Getoor |
| 2021 | Coherent and Consistent Relational Transfer Learning with Auto-encoders. | Harald Strmfelt, Luke Dickens, Artur S. d'Avila Garcez, Alessandra Russo |
| 2021 | Learning Arithmetic from Handwritten Images with the Aid of Symbols. | Daniel L. Silver, Ahmed Galila |
| 2021 | Neural Semirings. | Pedro Zuidberg Dos Martires |
| 2021 | Elite BackProp: Training Sparse Interpretable Neurons. | Theodoros Kasioumis, Joe Townsend, Hiroya Inakoshi |
| 2021 | Explainable Diabetic Retinopathy Classification Based on Neural-Symbolic Learning. | Se-In Jang, Michael J. A. Girard, Alexandre H. Thiry |
| 2021 | An Insect-Inspired Randomly, Weighted Neural Network with Random Fourier Features For Neuro-Symbolic Relational Learning. | Jinyung Hong, Theodore P. Pavlic |
151–175 of 250← PreviousNext →
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