Neuro-Symbolic Class Expression Learning

IJCAI 2023

Neuro-Symbolic AI, Deep Reinforcement Learning, and Description Logics

Clifford Embeddings - A Generalized Approach for Embedding in Normed Algebras

ECML 2023

Clifford Algebra and Representation Learning

LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals

ECML 2023

Multi-Hop Reasoning and Numeric Literals

Neural Class Expression Synthesis in ALCHIQ(D)

ECML 2023

Description Logics and Neural Networks

Learning Permutation-Invariant Embeddings for Description Logic Concepts

IDA 2023

Description Logic Concept Learning in a Continuous Domain

Conformal Credal Self-Supervised Learning

ICML 2022 (Distribution-Free Uncertainty Quantification)

Calibrated and less error-prone supervision for unlabeled data

EvoLearner

WWW 2022

Learning Description Logic Expressions and Evolutionary Algorithms

Rapid Explainability for Skill Description Learning

ISWC 2022

Deep Reinforcement Learning and Description Logics

Hardware-agnostic Computation for Large-scale Knowledge Graph Embeddings

SIMPAC 2022

Hardware-agnostic & Distributed computing for KGEs

Kronecker Decomposition for Embeddings

HT 2022

Data Compression via Dynamic Decomposition

CLIP

ESWC 2022

Learning Concept Lengths Accelerates Concept Learning in ALC

Convolutional Hypercomplex Embeddings

ACML 2021

Quaternions, Octonions, Convolutions, Knowledge Graphs, Embeddings, Link Prediction

Convolutional Complex Embeddings

ESWC-2021

Complex valued-embeddings, Convolutions, Affine Transformation, Ensembles, Link Prediction

Shallow Neural Model For Relation Prediction

IEEE-ICSC 2021

Shallow Neural Model For Relation Prediction

Compendium of Neurosymbolic Artificial Intelligence

Chapter 13:Class Expression Learning with Multiple Representations

Dice-Embeddings

Hardware-agnostic Framework for Large-scale Knowledge Graph Embeddings, Large-scale Machine Learning

Ontolearn

OWL Class Expressions Learning in Python

OWLAPY

OWL Engineering & Reasoning in Python

MLE vs MAP

Maximum Likelihood Estimation, Maximum A Posteriori Probability Estimation.

Support Vector Machines

Support Vector Machines, Quadratic Optimization Problem

Kernels

Regression on Steroids

Gaussian Process

Regression under uncertainty, Covariance and Kernel Matrix

Decision Tree, Bagging, Random Forest

Bias-Variance Decomposition, Recursive Decision Construction, Out-of-Bag Error

Boosting, AdaBoost

Gradient Descent in function space

Linear Classification

Maximum Margin Classifier, Softmax Classifier.

SVD in Love

Singular Value Decomposition, Dimensionality Reduction, Eigenvector, Eigenvalue and beautiful Rome

Understanding Bayesian Networks

Bayesian Networks

Benchmarking Frameworks

JAX vs Pytorch vs MXNet vs Numpy vs Numba

Computation Graphs

Computation Graphs & Backpropagation

Conv Nets

Backpropagation in convolutions

Graph Convolutional Nets

You are the average of your neighbors, GCN forward and backward

Batch Normalization

Backward pass in batch normalization, normalization as a differential function.

Nets, Optimizers and Object Oriented Programming

Computational Graphs, Forward and Backward computation flows.

SGD vs Momentum vs Adagrad vs RMSprob vs ADAM

Optimizers from scratch.

Vanilla Nets

Linear models vs Nets, Visualisation of decision boundaries