50 citations · 121 across the 35 of their papers we have counts for
5 papers · 1 filter
A Novel Technique for Evidence based Conditional Inference in Deep Neural Networks via Latent Feature Perturbation
Dinesh Khandelwal, Suyash Agrawal, Parag Singla +1
Auxiliary information can be exploited in machine learning models using the paradigm of evidence based conditional inference. Multi-modal techniques in Deep Neural Networks (DNNs)…
Block-Value Symmetries in Probabilistic Graphical Models
Gagan Madan, Ankit Anand, Mausam +1
One popular way for lifted inference in probabilistic graphical models is to first merge symmetric states into a single cluster (orbit) and then use these for downstream inference,…
Lifted Marginal MAP Inference
Vishal Sharma, Noman Ahmed Sheikh, Happy Mittal +2
Lifted inference reduces the complexity of inference in relational probabilistic models by identifying groups of constants (or atoms) which behave symmetric to each other. A number…
Domain Aware Markov Logic Networks
Happy Mittal, Ayush Bhardwaj, Vibhav Gogate +1
Combining logic and probability has been a long stand- ing goal of AI research. Markov Logic Networks (MLNs) achieve this by attaching weights to formulas in first-order logic, and…
Towards Understanding and Answering Multi-Sentence Recommendation Questions on Tourism
Danish Contractor, Barun Patra, Mausam Singla +1
We introduce the first system towards the novel task of answering complex multisentence recommendation questions in the tourism domain. Our solution uses a pipeline of two modules:…