Code for the model presented in the paper: "code2seq: Generating Sequences from Structured Representations of Code"
#计算机科学#This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily adap...
Lanczos Network, Graph Neural Networks, Deep Graph Convolutional Networks, Deep Learning on Graph Structured Data, QM8 Quantum Chemistry Benchmark, ICLR 2019
翻译 - Lanczos网络,图神经网络,深图卷积网络,图结构数据的深度学习,QM8量子化学基准测试,ICLR 2019
PyTorch code for ICLR 2019 paper: Self-Monitoring Navigation Agent via Auxiliary Progress Estimation
#计算机科学#[ICLR'19] Meta-learning with differentiable closed-form solvers
Official PyTorch implementation of Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation (ICLR 2019)
A simplified PyTorch implementation of GANsynth
The Reinforcement-Learning-Related Papers of ICLR 2019
#计算机科学#Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019
#计算机科学#Code for the paper 'Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology'
#自然语言处理#✂️ Repository for our ICLR 2019 paper: Discovery of Natural Language Concepts in Individual Units of CNNs
PyTorch implementation of "Variational Autoencoders with Jointly Optimized Latent Dependency Structure" [ICLR 2019]
We propose a Seed-Augment-Train/Transfer (SAT) framework that contains a synthetic seed image dataset generation procedure for languages with different numeral systems using freely available open font...
#自然语言处理#Implementation of https://arxiv.org/pdf/1805.12352.pdf (ICLR 2019)