Publications (12)
Meta-MeTTa: an operational semantics for MeTTa
Lucius Gregory Meredith, Ben Goertzel, Jonathan Warrell +1
We present an operational semantics for the language MeTTa.
Quantum Computing at the Frontiers of Biological Sciences
Prashant S. Emani, Jonathan Warrell, Alan Anticevic +15
The search for meaningful structure in biological data has relied on cutting-edge advances in computational technology and data science methods. However, challenges arise as we pus…
-QVAE: A Quantum Variational Autoencoder utilizing Regularized Mixed-state Latent Representations
Gaoyuan Wang, Jonathan Warrell, Prashant S. Emani +1
A major challenge in quantum computing is its application to large real-world datasets due to scarce quantum hardware resources. One approach to enabling tractable quantum models f…
Logical Guidance for the Exact Composition of Diffusion Models
Francesco Alesiani, Jonathan Warrell, Tanja Bien +3
We propose LOGDIFF (Logical Guidance for the Exact Composition of Diffusion Models), a guidance framework for diffusion models that enables principled constrained generation with c…
MPP-GNN: Subject-Adaptive Community Detection for fMRI-Based Alzheimer's Disease Classification
Yang Zhang, Xiao Zhou, Jonathan Warrell +3
Functional magnetic resonance imaging (fMRI) is a widely used technique for studying the brain. Recent methods that utilize graph neural networks (GNNs) for analysis of brain funct…
ImageSpirit: Verbal Guided Image Parsing
Ming-Ming Cheng, Shuai Zheng, Wen-Yan Lin +6
Humans describe images in terms of nouns and adjectives while algorithms operate on images represented as sets of pixels. Bridging this gap between how humans would like to access…
Rank Projection Trees for Multilevel Neural Network Interpretation
Jonathan Warrell, Hussein Mohsen, Mark Gerstein
A variety of methods have been proposed for interpreting nodes in deep neural networks, which typically involve scoring nodes at lower layers with respect to their effects on the o…
Variational methods for Learning Multilevel Genetic Algorithms using the Kantorovich Monad
Jonathan Warrell, Francesco Alesiani, Cameron Smith +2
Levels of selection and multilevel evolutionary processes are essential concepts in evolutionary theory, and yet there is a lack of common mathematical models for these core ideas.…
A Tiered Move-making Algorithm for General Non-submodular Pairwise Energies
Vibhav Vineet, Jonathan Warrell, Philip H. S. Torr
A large number of problems in computer vision can be modelled as energy minimization problems in a Markov Random Field (MRF) or Conditional Random Field (CRF) framework. Graph-cuts…
Efficient Privacy-Preserving Training of Quantum Neural Networks by Using Mixed States to Represent Input Data Ensembles
Gaoyuan Wang, Jonathan Warrell, Mark Gerstein
Quantum neural networks (QNNs) are gaining increasing interest due to their potential to detect complex patterns in data by leveraging uniquely quantum phenomena. This makes them p…
A meta-probabilistic-programming language for bisimulation of probabilistic and non-well-founded type systems
Jonathan Warrell, Alexey Potapov, Adam Vandervorst +1
We introduce a formal meta-language for probabilistic programming, capable of expressing both programs and the type systems in which they are embedded. We are motivated here by the…
Higher-Order Generalization Bounds: Learning Deep Probabilistic Programs via PAC-Bayes Objectives
Jonathan Warrell, Mark Gerstein
Deep Probabilistic Programming (DPP) allows powerful models based on recursive computation to be learned using efficient deep-learning optimization techniques. Additionally, DPP of…