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07/31/2023
Detecting the Anomalies in LiDAR Pointcloud
LiDAR sensors play an important role in the perception stack of modern a...
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03/25/2023
Causal Image Synthesis of Brain MR in 3D
Clinical decision making requires counterfactual reasoning based on a fa...
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01/31/2023
Transformers Meet Directed Graphs
Transformers were originally proposed as a sequence-to-sequence model fo...
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02/08/2022
Competition-Level Code Generation with AlphaCode
Programming is a powerful and ubiquitous problem-solving tool. Developin...
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12/10/2021
Association study between gene expression and multiple phenotypes in omics applications of complex diseases
Studying phenotype-gene association can uncover mechanism of diseases an...
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08/25/2021
ETA Prediction with Graph Neural Networks in Google Maps
Travel-time prediction constitutes a task of high importance in transpor...
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07/20/2021
WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset
We present a new dataset of Wikipedia articles each paired with a knowle...
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05/06/2021
Computer-Aided Design as Language
Computer-Aided Design (CAD) applications are used in manufacturing to mo...
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12/23/2020
Solving Mixed Integer Programs Using Neural Networks
Mixed Integer Programming (MIP) solvers rely on an array of sophisticate...
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07/07/2020
Strong Generalization and Efficiency in Neural Programs
We study the problem of learning efficient algorithms that strongly gene...
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06/28/2020
Scalable Deep Generative Modeling for Sparse Graphs
Learning graph generative models is a challenging task for deep learning...
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12/05/2019
A sparse negative binomial mixture model for clustering RNA-seq count data
Clustering with variable selection is a challenging but critical task fo...
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12/04/2019
Prioritized Unit Propagation with Periodic Resetting is (Almost) All You Need for Random SAT Solving
We propose prioritized unit propagation with periodic resetting, which i...
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10/28/2019
Learning Transferable Graph Exploration
This paper considers the problem of efficient exploration of unseen envi...
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10/02/2019
Efficient Graph Generation with Graph Recurrent Attention Networks
We propose a new family of efficient and expressive deep generative mode...
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09/04/2019
Simultaneous Estimation of Number of Clusters and Feature Sparsity in Clustering High-Dimensional Data
Estimating the number of clusters (K) is a critical and often difficult ...
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06/27/2019
Fast Training of Sparse Graph Neural Networks on Dense Hardware
Graph neural networks have become increasingly popular in recent years d...
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06/11/2019
Graph Convolutional Transformer: Learning the Graphical Structure of Electronic Health Records
Effective modeling of electronic health records (EHR) is rapidly becomin...
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05/07/2019
REGAL: Transfer Learning For Fast Optimization of Computation Graphs
We present a deep reinforcement learning approach to optimizing the exec...
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04/29/2019
Graph Matching Networks for Learning the Similarity of Graph Structured Objects
This paper addresses the challenging problem of retrieval and matching o...
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12/04/2018
Compositional Imitation Learning: Explaining and executing one task at a time
We introduce a framework for Compositional Imitation Learning and Execut...
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08/24/2018
Proximal Policy Optimization and its Dynamic Version for Sequence Generation
In sequence generation task, many works use policy gradient for model op...
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06/05/2018
Relational Deep Reinforcement Learning
We introduce an approach for deep reinforcement learning (RL) that impro...
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06/04/2018
Relational inductive biases, deep learning, and graph networks
Artificial intelligence (AI) has undergone a renaissance recently, makin...
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03/08/2018
Learning Deep Generative Models of Graphs
Graphs are fundamental data structures which concisely capture the relat...
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07/19/2017
Imagination-Augmented Agents for Deep Reinforcement Learning
We introduce Imagination-Augmented Agents (I2As), a novel architecture f...
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07/19/2017
Learning model-based planning from scratch
Conventional wisdom holds that model-based planning is a powerful approa...
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06/19/2017
Dualing GANs
Generative adversarial nets (GANs) are a promising technique for modelin...
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01/15/2017
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
We study characteristics of receptive fields of units in deep convolutio...
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11/17/2015
Gated Graph Sequence Neural Networks
Graph-structured data appears frequently in domains including chemistry,...
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11/03/2015
The Variational Fair Autoencoder
We investigate the problem of learning representations that are invarian...
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02/10/2015
Generative Moment Matching Networks
We consider the problem of learning deep generative models from data. We...
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12/17/2014
Learning unbiased features
A key element in transfer learning is representation learning; if repres...
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10/21/2014