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02/02/2023
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics
Molecular dynamics (MD) simulation is a widely used technique to simulat...
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06/14/2022
Exploring Representation of Horn Clauses using GNNs (technique report)
Learning program semantics from raw source code is challenging due to th...
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01/28/2022
HEAT: Hyperedge Attention Networks
Learning from structured data is a core machine learning task. Commonly,...
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06/18/2021
Learning to Generate Code Sketches
Traditional generative models are limited to predicting sequences of ter...
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05/26/2021
Self-Supervised Bug Detection and Repair
Machine learning-based program analyses have recently shown the promise ...
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03/05/2021
Learning to Extend Molecular Scaffolds with Structural Motifs
Recent advancements in deep learning-based modeling of molecules promise...
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06/08/2020
Copy that! Editing Sequences by Copying Spans
Neural sequence-to-sequence models are finding increasing use in editing...
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12/17/2019
Analyzing Privacy Loss in Updates of Natural Language Models
To continuously improve quality and reflect changes in data, machine lea...
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11/04/2019
Inferring Lower Runtime Bounds for Integer Programs
We present a technique to infer lower bounds on the worst-case runtime c...
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10/12/2019
Disentangling Interpretable Generative Parameters of Random and Real-World Graphs
While a wide range of interpretable generative procedures for graphs exi...
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09/20/2019
CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
Semantic code search is the task of retrieving relevant code given a nat...
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06/28/2019
GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation
This paper presents a new Graph Neural Network (GNN) type using feature-...
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06/26/2019
Program Synthesis and Semantic Parsing with Learned Code Idioms
Program synthesis of general-purpose source code from natural language s...
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11/05/2018
Structured Neural Summarization
Summarization of long sequences into a concise statement is a core probl...
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10/31/2018
Learning to Represent Edits
We introduce the problem of learning distributed representations of edit...
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07/09/2018
Robust Text-to-SQL Generation with Execution-Guided Decoding
We consider the problem of neural semantic parsing, which translates nat...
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07/09/2018
Execution-Guided Neural Program Decoding
We present a neural semantic parser that translatesnatural language ques...
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05/23/2018
Constrained Graph Variational Autoencoders for Molecule Design
Graphs are ubiquitous data structures for representing interactions betw...
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05/22/2018
Generative Code Modeling with Graphs
Generative models for source code are an interesting structured predicti...
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03/16/2018
Graph Partition Neural Networks for Semi-Supervised Classification
We present graph partition neural networks (GPNN), an extension of graph...
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11/01/2017
Learning to Represent Programs with Graphs
Learning tasks on source code (i.e., formal languages) have been conside...
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12/02/2016
Summary - TerpreT: A Probabilistic Programming Language for Program Induction
We study machine learning formulations of inductive program synthesis; t...
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08/15/2016
TerpreT: A Probabilistic Programming Language for Program Induction
We study machine learning formulations of inductive program synthesis; g...
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11/17/2015