143 citations · 1.1k across the 106 of their papers we have counts for
20 papers · 1 filter
High Dimensional Level Set Estimation with Bayesian Neural Network
Huong Ha, Sunil Gupta, Santu Rana +1
Level Set Estimation (LSE) is an important problem with applications in various fields such as material design, biotechnology, machine operational testing, etc. Existing techniques…
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization
Kien Do, Truyen Tran, Svetha Venkatesh
We propose two generic methods for improving semi-supervised learning (SSL). The first integrates weight perturbation (WP) into existing "consistency regularization" (CR) based met…
Logically Consistent Loss for Visual Question Answering
Anh-Cat Le-Ngo, Truyen Tran, Santu Rana +2
Given an image, a back-ground knowledge, and a set of questions about an object, human learners answer the questions very consistently regardless of question forms and semantic tas…
Sub-linear Regret Bounds for Bayesian Optimisation in Unknown Search Spaces
Hung Tran-The, Sunil Gupta, Santu Rana +2
Bayesian optimisation is a popular method for efficient optimisation of expensive black-box functions. Traditionally, BO assumes that the search space is known. However, in many pr…
Hierarchical Conditional Relation Networks for Multimodal Video Question Answering
Thao Minh Le, Vuong Le, Svetha Venkatesh +1
Video QA challenges modelers in multiple fronts. Modeling video necessitates building not only spatio-temporal models for the dynamic visual channel but also multimodal structures…
Neurocoder: Learning General-Purpose Computation Using Stored Neural Programs
Hung Le, Svetha Venkatesh
Artificial Neural Networks are uniquely adroit at machine learning by processing data through a network of artificial neurons. The inter-neuronal connection weights represent the l…