xenialll Goto Github PK

iaf

Code for reproducing key results in the paper "Improving Variational Inference with Inverse Autoregressive Flow"

iaptt-gm

Code Repository for NeurIPS 2021 accepted paper, named "Torwards Gradient-based Bilevel Optimization with non-convex Followers and Beyond"

incremental-gnns

Incremental Training of Graph Neural Networks on Temporal Graphs under Distribution Shift

invertible-zero-shot-recognition-flows

l-marvel

lifelong-learning

Lifelong Learning of Graph Neural Networks for Open-World Node Classification

lstm

understand lstm and things like this

m2m

Code for the paper "M2m: Imbalanced Classification via Major-to-minor Translation" (CVPR 2020)

mae

PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

man-sf

Reproduction of the paper "Deep Attentive Learning for Stock Movement Prediction From Social Media Text and Company Correlations"

mtdnn

Multi-scale Two-way Deep Neural Network

neural-function-distributions

Pytorch implementation of Generative Models as Distributions of Functions 🌿

nlp_clip_pytorch

star_transformer pytorch

noise_flow

Noise Flow: Noise Modeling with Conditional Normalizing Flows

occo

[ICCV' 21] "Unsupervised Point Cloud Pre-training via Occlusion Completion"

ood_federated_learning

outlier-exposure

Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

overnight-stock-movement-prediction

patrickmanagementsystem

第一次提交乐鲜生活馆后台软件。

ppgencdr

This repository is the implementation of AAAI 2023: PPGenCDR

prior-lt

profit-naacl

Code for PROFIT: Quantitative Day Trading From Natural Language Using Reinforcement Learning at NAACL 2021

pytorch-stocknet

qlib

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib.

saa-sequence-alignment-algorithm-

shift-robust-gnns

"Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')

solved-by-flexbox

A showcase of problems once hard or impossible to solve with CSS alone, now made trivially easy with Flexbox.

srflow

Official SRFlow training code: Super-Resolution using Normalizing Flow in PyTorch

srflow-pytorch

[WIP] pytorch implementation of paper "SRFlow: Learning the Super-Resolution Space with Normalizing Flow"

stark

[ICCV'21] Learning Spatio-Temporal Transformer for Visual Tracking