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2021-12
Learning Generalized Gumbel-max Causal Mechanisms
PLUR: A Unifying, Graph-Based View of Program Learning, Understanding, and Repair
Structured Denoising Diffusion Models in Discrete State-Spaces
Learning to Combine Per-Example Solutions for Neural Program Synthesis
2021-06
Beyond In-Place Corruption: Insertion and Deletion In Denoising Probabilistic Models
2021-05
Learning to Extend Program Graphs to Work-in-Progress Code.
2020-12
Tabular: Probabilistic Inference from the Spreadsheet
2020-11
OPTIMIZING SPARSE GRAPH NEURAL NETWORKS FOR DENSE HARDWARE
2020-07
Learning Graph Structure With A Finite-State Automaton Layer
Software Engineering Event Modeling using Relative Time in Temporal Knowledge Graphs.
2020-06
Learning to Fix Build Errors with Graph2Diff Neural Networks
Gradient Estimation with Stochastic Softmax Tricks
2020-04
LEARNING EXECUTION THROUGH NEURAL CODE FUSION
2020-03
On-the-Fly Adaptation of Source Code Models using Meta-Learning
2020-01
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks
Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces
2019-09
Fast Training of Sparse Graph Neural Networks on Dense Hardware
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