• Stars
    star
    91
  • Rank 366,013 (Top 8 %)
  • Language
    Python
  • License
    MIT License
  • Created about 4 years ago
  • Updated over 2 years ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"

More Repositories

1

code2vec

TensorFlow code for the neural network presented in the paper: "code2vec: Learning Distributed Representations of Code"
Python
1,092
star
2

code2seq

Code for the model presented in the paper: "code2seq: Generating Sequences from Structured Representations of Code"
Python
547
star
3

how_attentive_are_gats

Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)
Python
299
star
4

RASP

An interpreter for RASP as described in the ICML 2021 paper "Thinking Like Transformers"
Python
279
star
5

Nero

Code and resources for the paper: "Neural Reverse Engineering of Stripped Binaries using Augmented Control Flow Graphs"
Python
185
star
6

slm-code-generation

TensorFlow code for the neural network presented in the paper: "Structural Language Models of Code" (ICML'2020)
Java
86
star
7

esh

statistical similarity of binaries (Esh)
C#
73
star
8

lstar_extraction

implementation of ICML 2018 paper, Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples
Jupyter Notebook
71
star
9

layer_norm_expressivity_role

Code for the paper "On the Expressivity Role of LayerNorm in Transformers' Attention" (Findings of ACL'2023)
Python
43
star
10

c3po

Code for the paper "A Structural Model for Contextual Code Changes"
Python
25
star
11

adversarial-examples

Code for the paper: "Adversarial Examples for Models of Code"
Python
17
star
12

weighted_lstar

implementation for "learning weighted deterministic automata from queries and counterexamples", neurips 2019
Python
17
star
13

RASP-exps

Code for running the transformers in the ICML 2021 paper "Thinking Like Transformers"
Python
16
star
14

prime

Java
14
star
15

safe

SAFE static analysis tools
Java
12
star
16

differential

differential
C
12
star
17

counting_dimensions

demonstration for our ACL 2018 paper, "On the Practical Computational Power of Finite Precision RNNs for Language Recognition"
Jupyter Notebook
10
star
18

id2vec

Python
9
star
19

RNN_to_PRS_CFG

Implementation of TACAS 2021 paper, "Extrapolating CFGs from RNNs"
Python
9
star
20

atam

Example programs for ATAM
C
3
star