research
∙
06/16/2023
Collapsed Inference for Bayesian Deep Learning
Bayesian neural networks (BNNs) provide a formalism to quantify and cali...
share
research
∙
10/04/2022
SIMPLE: A Gradient Estimator for k-Subset Sampling
k-subset sampling is ubiquitous in machine learning, enabling regulariza...
research
∙
02/21/2021
Tractable Computation of Expected Kernels by Circuits
Computing the expectation of some kernel function is ubiquitous in machi...
research
∙
02/28/2020
Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing
Weighted model integration (WMI) is a very appealing framework for proba...
research
∙
09/20/2019
Hybrid Probabilistic Inference with Logical Constraints: Tractability and Message-Passing
Weighted model integration (WMI) is a very appealing framework for proba...
research
∙
03/13/2019
Efficient Search-Based Weighted Model Integration
Weighted model integration (WMI) extends Weighted model counting (WMC) t...
research
∙
11/20/2017