27 citations · 64 across the 44 of their papers we have counts for
6 papers · 1 filter
Pearl Causal Hierarchy on Image Data: Intricacies & Challenges
Matej Zečević, Moritz Willig, Devendra Singh Dhami +1
Many researchers have voiced their support towards Pearl's counterfactual theory of causation as a stepping stone for AI/ML research's ultimate goal of intelligent systems. As in a…
Neural Meta-Symbolic Reasoning and Learning
Zihan Ye, Hikaru Shindo, Devendra Singh Dhami +1
Deep neural learning uses an increasing amount of computation and data to solve very specific problems. By stark contrast, human minds solve a wide range of problems using a fixed…
LogicRank: Logic Induced Reranking for Generative Text-to-Image Systems
Björn Deiseroth, Patrick Schramowski, Hikaru Shindo +2
Text-to-image models have recently achieved remarkable success with seemingly accurate samples in photo-realistic quality. However as state-of-the-art language models still struggl…
FEATHERS: Federated Architecture and Hyperparameter Search
Jonas Seng, Pooja Prasad, Martin Mundt +2
Deep neural architectures have profound impact on achieved performance in many of today's AI tasks, yet, their design still heavily relies on human prior knowledge and experience.…
Can Foundation Models Talk Causality?
Moritz Willig, Matej Zečević, Devendra Singh Dhami +1
Foundation models are subject to an ongoing heated debate, leaving open the question of progress towards AGI and dividing the community into two camps: the ones who see the arguabl…
Towards a Solution to Bongard Problems: A Causal Approach
Salahedine Youssef, Matej Zečević, Devendra Singh Dhami +1
Even though AI has advanced rapidly in recent years displaying success in solving highly complex problems, the class of Bongard Problems (BPs) yet remain largely unsolved by modern…