45 citations · 213 across the 48 of their papers we have counts for
8 papers · 1 filter
A Solver-Free Framework for Scalable Learning in Neural ILP Architectures
Yatin Nandwani, Rishabh Ranjan, Mausam +1
There is a recent focus on designing architectures that have an Integer Linear Programming (ILP) layer within a neural model (referred to as Neural ILP in this paper). Neural ILP a…
Neural Models for Output-Space Invariance in Combinatorial Problems
Yatin Nandwani, Vidit Jain, Mausam +1
Recently many neural models have been proposed to solve combinatorial puzzles by implicitly learning underlying constraints using their solved instances, such as sudoku or graph co…
Neural Learning of One-of-Many Solutions for Combinatorial Problems in Structured Output Spaces
Yatin Nandwani, Deepanshu Jindal, Mausam +1
Recent research has proposed neural architectures for solving combinatorial problems in structured output spaces. In many such problems, there may exist multiple solutions for a gi…
Knowledge Base Completion: Baseline strikes back (Again)
Prachi Jain, Sushant Rathi, Mausam +1
Knowledge Base Completion (KBC) has been a very active area lately. Several recent KBCpapers propose architectural changes, new training methods, or even new formulations. KBC syst…
Unsupervised Learning of KB Queries in Task-Oriented Dialogs
Dinesh Raghu, Nikhil Gupta, Mausam
Task-oriented dialog (TOD) systems often need to formulate knowledge base (KB) queries corresponding to the user intent and use the query results to generate system responses. Exis…
Symbolic Network: Generalized Neural Policies for Relational MDPs
Sankalp Garg, Aniket Bajpai, Mausam
A Relational Markov Decision Process (RMDP) is a first-order representation to express all instances of a single probabilistic planning domain with possibly unbounded number of obj…