F.bear's starred repositories
state-of-the-art-result-for-machine-learning-problems
This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.
build-your-own-x
Master programming by recreating your favorite technologies from scratch.
deep-reinforcement-learning
Repo for the Deep Reinforcement Learning Nanodegree program
GenericObjectDecoding
Demo code for Horikawa and Kamitani (2017) Generic decoding of seen and imagined objects using hierarchical visual features. Nat Commun https://www.nature.com/articles/ncomms15037.
DeepImageReconstruction
Data and code for Shen, Horikawa, Majima, and Kamitani (2019) Deep image reconstruction from human brain activity. PLoS Comput. Biol. http://dx.doi.org/10.1371/journal.pcbi.1006633.
python-guide
Python best practices guidebook, written for humans.
json-viewer
Display JSON file as tree in GUI
deepxplore
DeepXplore code release
bibtex-normalizer
Bibtex Normalizer - Normalizing BibTeX entries to a common format
biblatex-gb7714-2015
A biblatex implementation of the GB/T7714-2015 bibliography style || GB/T 7714-2015 参考文献著录和标注的biblatex样式包
adversarial-squad
Code from Jia and Liang, "Adversarial Examples for Evaluating Reading Comprehension Systems" (EMNLP 2017)
dynamic-coattention-network
Tensorflow implementation of Dynamic Coattention Networks for Question Answering.
language_models
A Keras rnn model trained on small wikipedia dataset that generates sentences
bi-att-flow
Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to achieve a query-aware context representation without early summarization.