mindojune Goto Github PK

a-hierarchical-latent-structure-for-variational-conversation-modeling

PyTorch Implementation of "A Hierarchical Latent Structure for Variational Conversation Modeling" (NAACL 2018 Oral)

academicpages.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

blog

:sparkling_heart: Things I care about :sparkling_heart:

c99demo

C99 demo, an interactive program for demonstrating how the C99 algorithm works, by Freddy Choi

cade

daedal

Daedal Decoupled Access-Execute LLVM Tools

depth_cnn

dialogrpt

EMNLP 2020: "Dialogue Response Ranking Training with Large-Scale Human Feedback Data" - fork of andrew's fork

dir-vhred

Dirichlet Latent Variable Hierarchical Recurrent Encoder-Decoder in dialogue generation（EMNLP2019）

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

grade_2021

grade_checklist

guidedlda

semi supervised guided topic model with custom guidedLDA

hedwig

PyTorch deep learning models for document classification

hred-latent-piecewise

kor-depparser

kor-transducer

mindojune.github.io

Dojune's Blog

mm-github-pages-starter

Minimal Mistakes GitHub Pages site starter

monodepth-pytorch

Unofficial implementation of Unsupervised Monocular Depth Estimation neural network MonoDepth in PyTorch

oldmindojune.github.io

Github Repository for Dojune's Blog

pytorch-cnn-finetune

Fine-tune pretrained Convolutional Neural Networks with PyTorch

revisiting_single_depth_estimation

official implementation of "Revisiting Single Image Depth Estimation: Toward Higher Resolution Maps with Accurate Object Boundaries"

sequential_sentence_classification

spanbert

Code for using and evaluating SpanBERT.

stylized-imagenet

Code to create Stylized-ImageNet, a stylized version of standard ImageNet (ICLR 2019 Oral)

text-segmentation

Implementation of the paper: Text Segmentation as a Supervised Learning Task

text_segment

texture-vs-shape

Pre-trained models, data, code & materials from the paper "ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness" (ICLR 2019 Oral)

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.