10 citations · 71 across the 49 of their papers we have counts for
7 papers · 1 filter
Logical Interpretations of Autoencoders
Anton Fuxjaeger, Vaishak Belle
The unification of low-level perception and high-level reasoning is a long-standing problem in artificial intelligence, which has the potential to not only bring the areas of logic…
The Quest for Interpretable and Responsible Artificial Intelligence
Vaishak Belle
Artificial Intelligence (AI) provides many opportunities to improve private and public life. Discovering patterns and structures in large troves of data in an automated manner is a…
Experiential AI
Drew Hemment, Ruth Aylett, Vaishak Belle +5
Experiential AI is proposed as a new research agenda in which artists and scientists come together to dispel the mystery of algorithms and make their mechanisms vividly apparent. I…
Implicitly Learning to Reason in First-Order Logic
Vaishak Belle, Brendan Juba
We consider the problem of answering queries about formulas of first-order logic based on background knowledge partially represented explicitly as other formulas, and partially rep…
A Correctness Result for Synthesizing Plans With Loops in Stochastic Domains
Laszlo Treszkai, Vaishak Belle
Finite-state controllers (FSCs), such as plans with loops, are powerful and compact representations of action selection widely used in robotics, video games and logistics. There ha…
Fairness in Machine Learning with Tractable Models
Michael Varley, Vaishak Belle
Machine Learning techniques have become pervasive across a range of different applications, and are now widely used in areas as disparate as recidivism prediction, consumer credit-…
Learning Credal Sum-Product Networks
Amelie Levray, Vaishak Belle
Probabilistic representations, such as Bayesian and Markov networks, are fundamental to much of statistical machine learning. Thus, learning probabilistic representations directly…