14 citations · 15 across the 4 of their papers we have counts for
4 papers
The Causal Loss: Driving Correlation to Imply Causation
Moritz Willig, Matej Zečević, Devendra Singh Dhami +1
Most algorithms in classical and contemporary machine learning focus on correlation-based dependence between features to drive performance. Although success has been observed in ma…
Relating Graph Neural Networks to Structural Causal Models
Matej Zečević, Devendra Singh Dhami, Petar Veličković +1
Causality can be described in terms of a structural causal model (SCM) that carries information on the variables of interest and their mechanistic relations. For most processes of…
Neuro-Symbolic Forward Reasoning
Hikaru Shindo, Devendra Singh Dhami, Kristian Kersting
Reasoning is an essential part of human intelligence and thus has been a long-standing goal in artificial intelligence research. With the recent success of deep learning, incorpora…
Sum-Product-Attention Networks: Leveraging Self-Attention in Probabilistic Circuits
Zhongjie Yu, Devendra Singh Dhami, Kristian Kersting
Probabilistic circuits (PCs) have become the de-facto standard for learning and inference in probabilistic modeling. We introduce Sum-Product-Attention Networks (SPAN), a new gener…