Added the neural reasoner paper

data/bib/dice.bib

@@ -8749,7 +8749,7 @@ @InProceedings{kamdemteyou2024
   month        = oct,
   organization = {CIKM24},
   abstract     = {We introduce a novel embedding method diverging from conventional approaches by operating within function spaces of finite dimension rather than finite vector space, thus departing significantly from standard knowledge graph embedding techniques. Initially employing polynomial functions to compute embeddings, we progress to more intricate representations using neural networks with varying layer complexities. We argue that employing functions for embedding computation enhances expressiveness and allows for more degrees of freedom, enabling operations such as composition, derivatives and primitive of entities representation. Additionally, we meticulously outline the step-by-step construction of our approach and provide code for reproducibility, thereby facilitating further exploration and application in the field.},
-  keywords     = {kamdem demir ngonga lemurproject 2024 dice},
+  keywords     = {kamdem demir ngonga enexa lemurproject dice},
   url          = {https://papers.dice-research.org/2024/CIKM_FMULT/public.pdf},
 }
 
@@ -8762,7 +8762,7 @@ @InProceedings{kamdemteyou2024a
   month        = oct,
   organization = {ECAI24},
   abstract     = {Clifford algebras are a natural extension of division algebras, including real numbers, complex numbers, quaternions, and octonions. Previous research in knowledge graph embeddings has focused exclusively on Clifford algebras of a specific type, which do not include nilpotent base vectors—elements that square to zero. In this work, we introduce a novel approach by incorporating nilpotent base vectors with a nilpotency index of two, leading to a more general form of Clifford algebras named degenerate Clifford algebras. This generalization to degenerate Clifford algebras does allow for covering dual numbers and as such include translations and rotations models under the same generalization paradigm for the first time. We develop two models to determine the parameters that define the algebra: one using a greedy search and another predicting the parameters based on neural network embeddings of the input knowledge graph. Our evaluation on seven benchmark datasets demonstrates that this incorporation of nilpotent vectors enhances the quality of embeddings. Additionally, our method outperforms state-of-the-art approaches in terms of generalization, particularly regarding the mean reciprocal rank achieved on validation data. Finally, we show that even a simple greedy search can effective},
-  keywords     = {kamdem demir ngonga lemurproject 2024 dice},
+  keywords     = {kamdem demir ngonga enexa lemurproject dice},
   url          = {https://papers.dice-research.org/2024/ECAI_DeCaL/public.pdf},
 }
 
@@ -9166,6 +9166,20 @@ @inproceedings{sapkota2025parameter
   keywords  = {dice sailproject kiowl enexa sapkota demir ngonga sharma}
 }
 
+@InProceedings{Teyou2025,
+  author    = {Louis Mozart {Kamdem Teyou} and Luke Friedrichs and N'Dah Jean Kouagou and Caglar Demir and Yasir Mahmood and Stefan Heindorf and Axel-Cyrille {Ngonga Ngomo}},
+  booktitle = {Proceedings of the Knowledge Capture Conference 2025 (K-CAP '25)},
+  title     = {Neural Reasoning for Robust Instance Retrieval in SHOIQ},
+  year      = {2025},
+  pages     = {1--8},
+  address   = {Dayton, OH, USA},
+  publisher = {ACM},
+  organization = {K-CAP},
+  doi       = {10.1145/3731443.3771348},
+  url       = {https://svn.dice-research.org/open/papers/2025/KCAP_EBR/public.pdf},
+  keywords = {kamdem demir ngonga luke kouagou friedrichs mahmood enexa lemurproject sailproject kiowl whale dice}
+}
+
 @InProceedings{vollmers2025eleval,
   author    = {Daniel Vollmers and Ren{\'e} Speck and Hamada M. Zahera and Axel{-}Cyrille Ngonga Ngomo},
   booktitle = {Proceedings of the 12th Knowledge Capture Conference 2025, {K-CAP} 2025, The Thirteenth International Conference on Knowledge Capture, December 10 - 12, 2025, Dayton, Ohio, USA},
@@ -9178,4 +9192,3 @@ @InProceedings{vollmers2025eleval
 
 
 
-