A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference

23 December 2022

Emile van Krieken

Thiviyan Thanapalasingam

Papers citing "A-NeSI: A Scalable Approximate Method for Probabilistic Neurosymbolic Inference"

34 / 34 papers shown

Title
CTSketch: Compositional Tensor Sketching for Scalable Neurosymbolic Learning Seewon Choi Alaia Solko-Breslin Rajeev Alur Eric Wong 37 0 0 31 Mar 2025
Noise to the Rescue: Escaping Local Minima in Neurosymbolic Local Search Alessandro Daniele Emile van Krieken 65 0 0 03 Mar 2025
Beyond the convexity assumption: Realistic tabular data generation under quantifier-free real linear constraints Mihaela C. Stoian Eleonora Giunchiglia 89 2 0 25 Feb 2025
Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens Samuele Bortolotti Emanuele Marconato Paolo Morettin Andrea Passerini Stefano Teso 61 2 0 16 Feb 2025
Neuro-Symbolic AI in 2024: A Systematic Review Brandon C. Colelough William Regli NAI 65 9 0 09 Jan 2025
Neuro-Symbolic AI: Explainability, Challenges, and Future Trends Xin Zhang Victor S. Sheng AI4TS 34 4 0 07 Nov 2024
Symbolic regression via MDLformer-guided search: from minimizing prediction error to minimizing description length Zihan Yu Jingtao Ding Yong Li 42 0 0 06 Nov 2024
LogiCity: Advancing Neuro-Symbolic AI with Abstract Urban Simulation Bowen Li Zhaoyu Li Qiwei Du Jinqi Luo Wenshan Wang ... Katia P. Sycara Pradeep Kumar Ravikumar Alexander G. Gray X. Si Sebastian A. Scherer AI4CE LRM 81 3 0 01 Nov 2024
Neuro-symbolic Learning Yielding Logical Constraints Zenan Li Yunpeng Huang Zhaoyu Li Yuan Yao Jingwei Xu Taolue Chen Xiaoxing Ma Jian Lu NAI 50 5 0 28 Oct 2024
A Fast Convoluted Story: Scaling Probabilistic Inference for Integer Arithmetic Lennert De Smet Pedro Zuidberg Dos Martires 19 1 0 16 Oct 2024
TL-PCA: Transfer Learning of Principal Component Analysis Sharon Hendy Yehuda Dar 161 1 0 14 Oct 2024
EXPLAIN, AGREE, LEARN: Scaling Learning for Neural Probabilistic Logic Victor Verreet Lennert De Smet Luc de Raedt Emanuele Sansone 25 0 0 15 Aug 2024
Data-Efficient Learning with Neural Programs Alaia Solko-Breslin Seewon Choi Ziyang Li Neelay Velingker Rajeev Alur Mayur Naik Eric Wong 29 5 0 10 Jun 2024
On the Hardness of Probabilistic Neurosymbolic Learning Jaron Maene Vincent Derkinderen Luc de Raedt 41 3 0 06 Jun 2024
Latent Logic Tree Extraction for Event Sequence Explanation from LLMs Zitao Song Chao Yang Chaojie Wang Bo An Shuang Li 60 4 0 03 Jun 2024
Learning diverse attacks on large language models for robust red-teaming and safety tuning Seanie Lee Minsu Kim Lynn Cherif David Dobre Juho Lee ... Kenji Kawaguchi Gauthier Gidel Yoshua Bengio Nikolay Malkin Moksh Jain AAML 63 12 0 28 May 2024
ULLER: A Unified Language for Learning and Reasoning Emile van Krieken Samy Badreddine Robin Manhaeve Eleonora Giunchiglia NAI 32 3 0 01 May 2024
On the Independence Assumption in Neurosymbolic Learning Emile van Krieken Pasquale Minervini E. Ponti Antonio Vergari 48 11 0 12 Apr 2024
PiShield: A PyTorch Package for Learning with Requirements Mihaela C. Stoian Alex Tatomir Thomas Lukasiewicz Eleonora Giunchiglia 28 1 0 28 Feb 2024
Improving Neural-based Classification with Logical Background Knowledge Arthur Ledaguenel Céline Hudelot M. Khouadjia NAI 44 1 0 20 Feb 2024
BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts Emanuele Marconato Samuele Bortolotti Emile van Krieken Antonio Vergari Andrea Passerini Stefano Teso 41 19 0 19 Feb 2024
Improved off-policy training of diffusion samplers Marcin Sendera Minsu Kim Sarthak Mittal Pablo Lemos Luca Scimeca Jarrid Rector-Brooks Alexandre Adam Yoshua Bengio Nikolay Malkin OffRL 66 17 0 07 Feb 2024
How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data Mihaela C. Stoian Salijona Dyrmishi Maxime Cordy Thomas Lukasiewicz Eleonora Giunchiglia 23 15 0 07 Feb 2024
Sandra -- A Neuro-Symbolic Reasoner Based On Descriptions And Situations Nicolas Lazzari S. D. Giorgis Aldo Gangemi Valentina Presutti 27 4 0 01 Feb 2024
Amortizing intractable inference in large language models Marvin Schmitt Moksh Jain Daniel Habermann Younesse Kaddar Ullrich Kothe Stefan T. Radev Nikolay Malkin AIFin BDL 29 46 0 06 Oct 2023
Pre-Training and Fine-Tuning Generative Flow Networks Ling Pan Moksh Jain Kanika Madan Yoshua Bengio 47 13 0 05 Oct 2023
Expected flow networks in stochastic environments and two-player zero-sum games Marco Jiralerspong Bilun Sun Danilo Vucetic Tianyu Zhang Yoshua Bengio Gauthier Gidel Nikolay Malkin 36 5 0 04 Oct 2023
Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts Emanuele Marconato Stefano Teso Antonio Vergari Andrea Passerini 38 30 0 31 May 2023
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets Dinghuai Zhang H. Dai Nikolay Malkin Aaron Courville Yoshua Bengio L. Pan 24 36 0 26 May 2023
Neuro-Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsal Emanuele Marconato G. Bontempo E. Ficarra Simone Calderara Andrea Passerini Stefano Teso NAI LRM CLL 35 20 0 02 Feb 2023
GFlowNets and variational inference Nikolay Malkin Salem Lahlou T. Deleu Xu Ji J. E. Hu Katie Everett Dinghuai Zhang Yoshua Bengio BDL 134 77 0 02 Oct 2022
Trajectory balance: Improved credit assignment in GFlowNets Nikolay Malkin Moksh Jain Emmanuel Bengio Chen Sun Yoshua Bengio 145 166 0 31 Jan 2022
Logic Tensor Networks Samy Badreddine Artur Garcez Luciano Serafini Michael Spranger NAI 70 199 0 25 Dec 2020
On Completeness-aware Concept-Based Explanations in Deep Neural Networks Chih-Kuan Yeh Been Kim Sercan Ö. Arik Chun-Liang Li Tomas Pfister Pradeep Ravikumar FAtt 122 297 0 17 Oct 2019