Articles in the publication category
Probabilistic Inference with Algebraic Constraints: Theoretical Limits and Practical Approximations
Imagining Grounded Conceptual Representations from Perceptual Information in Situated Guessing Games
Handling Missing Data in Decision Trees: A Probabilistic Approach
Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits
Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing
Conditional Sum-Product Networks: Imposing Structure on Deep Probabilistic Architectures
Strudel: Learning Structured-Decomposable Probabilistic Circuits
From Variational to Deterministic Autoencoders
Hybrid Probabilistic Inference with Logical Constraints: Tractability and Message-Passing
On Tractable Computation of Expected Predictions
Automatic Bayesian density analysis
Random Sum-Product Networks: A Simple and Effective Approach to Probabilistic Deep Learning
Visualizing and understanding Sum-Product Networks
Ensembles of density estimators for positive-unlabeled learning
Sum-product autoencoding: Encoding and decoding representations using sum-product networks
Mixed sum-product networks: A deep architecture for hybrid domains
Bayesian Nonparametric Hawkes Processes
Sum-Product Network structure learning by efficient product nodes discovery
Fast and Accurate Density Estimation with Extremely Randomized Cutset Networks
Encoding and Decoding Representations with Sum- and Max-Product Networks
End-to-end Learning of Deep Spatio-temporal Representations for Satellite Image Time Series Classification
Alternative Variable Splitting Methods to Learn Sum-Product Networks
Generative Probabilistic Models for Positive-Unlabeled Learning
Towards Representation Learning with Tractable Probabilistic Models
Multi-Label Classification with Cutset Networks
Learning Bayesian Random Cutset Forests
Learning Accurate Cutset Networks by Exploiting Decomposability
Simplifying, Regularizing and Strengthening Sum-Product Network Structure Learning
Handling Incomplete Heterogeneous Data using VAEs