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05/23/2023
Image Manipulation via Multi-Hop Instructions – A New Dataset and Weakly-Supervised Neuro-Symbolic Approach
We are interested in image manipulation via natural language text – a ta...
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11/12/2022
Learning Neuro-symbolic Programs for Language Guided Robot Manipulation
Given a natural language instruction, and an input and an output scene, ...
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10/17/2022
A Solver-Free Framework for Scalable Learning in Neural ILP Architectures
There is a recent focus on designing architectures that have an Integer ...
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02/07/2022
Neural Models for Output-Space Invariance in Combinatorial Problems
Recently many neural models have been proposed to solve combinatorial pu...
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10/14/2021
A Simple, Strong and Robust Baseline for Distantly Supervised Relation Extraction
Distantly supervised relation extraction (DS-RE) is generally framed as ...
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07/16/2021
Towards an Interpretable Latent Space in Structured Models for Video Prediction
We focus on the task of future frame prediction in video governed by und...
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07/16/2021
ScRAE: Deterministic Regularized Autoencoders with Flexible Priors for Clustering Single-cell Gene Expression Data
Clustering single-cell RNA sequence (scRNA-seq) data poses statistical a...
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04/18/2021
CEAR: Cross-Entity Aware Reranker for Knowledge Base Completion
Pre-trained language models (LMs) like BERT have shown to store factual ...
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09/28/2020
Joint Spatio-Textual Reasoning for Answering Tourism Questions
Our goal is to answer real-world tourism questions that seek Points-of-I...
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08/27/2020
Neural Learning of One-of-Many Solutions for Combinatorial Problems in Structured Output Spaces
Recent research has proposed neural architectures for solving combinator...
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06/10/2020
To Regularize or Not To Regularize? The Bias Variance Trade-off in Regularized AEs
Regularized Auto-Encoders (AE) form a rich class of methods within the l...
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12/10/2019
Towards Latent Space Optimality for Auto-Encoder Based Generative Models
The field of neural generative models is dominated by the highly success...
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09/08/2019
Large Scale Question Answering using Tourism Data
Real world question answering can be significantly more complex than wha...
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08/02/2019
CVC4-SymBreak: Derived SMT solver at SMT Competition 2019
We present CVC4-SymBreak, a derived SMT solver based on CVC4, and a non-...
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11/24/2018
Exploiting Test Time Evidence to Improve Predictions of Deep Neural Networks
Many prediction tasks, especially in computer vision, are often inherent...
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07/03/2018
Domain Aware Markov Logic Networks
Combining logic and probability has been a long standing goal of AI. Mar...
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07/02/2018
Block-Value Symmetries in Probabilistic Graphical Models
Several lifted inference algorithms for probabilistic graphical models f...
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07/02/2018
Lifted Marginal MAP Inference
Lifted inference reduces the complexity of inference in relational proba...
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01/05/2018
Towards Understanding and Answering Multi-Sentence Recommendation Questions on Tourism
We introduce the first system towards the novel task of answering comple...
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07/27/2017
Non-Count Symmetries in Boolean & Multi-Valued Prob. Graphical Models
Lifted inference algorithms commonly exploit symmetries in a probabilist...
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07/22/2017
Coarse-to-Fine Lifted MAP Inference in Computer Vision
There is a vast body of theoretical research on lifted inference in prob...
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06/30/2016
Lifted Region-Based Belief Propagation
Due to the intractable nature of exact lifted inference, research has re...
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06/30/2016
