.- Context Helps: Integrating context information with videos in a graph-based HAR framework.
.- Assessing Logical Reasoning Capabilities of Encoder-Only Transformer Models.
.- Variable Assignment Invariant Neural Networks for Learning Logic Programs.
.- ViPro: Enabling and Controlling Video Prediction for Complex Dynamical Scenarios using Procedural Knowledge.
.- The Role of Foundation Models in Neuro-Symbolic Learning and Reasoning.
.- A semantic loss for ontology classification.
.- On the use of Neurosymbolic AI for Defending against Cyber Attacks.
.- Bayesian Inverse Graphics for Few-Shot Concept Learning.
.- Simple and Effective Transfer Learning for Neuro-Symbolic Integration.
.- Ethical Reward Machines.
.- Embed2Rule - Scalable Neuro-Symbolic Learning via Latent Space Weak-Labelling.
.- ULLER: A Unified Language for Learning and Reasoning.
.- Disentangling Visual Priors: Unsupervised Learning of Scene Interpretations with Compositional Autoencoder.
.- Probing LLMs for logical reasoning.
.- Enhancing Machine Learning Predictions through Knowledge Graph Embeddings.
.- Terminating Differentiable Tree Experts.
.- Valid Text-to-SQL Generation with Unification-based DeepStochLog.
.- Enhancing Geometric Ontology Embeddings for EL++ with Negative Sampling and Deductive Closure Filtering.
.- Lattice-preserving ALC ontology embeddings.
.- Towards Learning Abductive Reasoning using VSA Distributed Representations.
.- Learning to Solve Abstract Reasoning Problems with Neurosymbolic Program Synthesis and Task Generation.
.- Leveraging Neurosymbolic AI for Slice Discovery.
