shrejais Goto Github PK

cse-250a-ai-probabilistic-reasoning-and-learning-

cvpr2021-papers-with-code

CVPR 2021 论文和开源项目合集

ddsp

DDSP: Differentiable Digital Signal Processing

deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

deep-learning-for-doa-estimation-with-random-sensor-positions

deep-learning-for-tracking-and-detection

Collection of papers, datasets, code and other resources for object tracking and detection using deep learning

deep-learning-keras-tf-tutorial

Learn deep learning with tensorflow2.0, keras and python through this comprehensive deep learning tutorial series. Learn deep learning from scratch. Deep learning series for beginners. Tensorflow tutorials, tensorflow 2.0 tutorial. deep learning tutorial python.

deep-learning-with-tensorflow-2-and-keras

Deep Learning with TensorFlow 2 and Keras, published by Packt

deep-reinforcement-learning-papers

A list of recent papers regarding deep reinforcement learning

deeplearning-models

A collection of various deep learning architectures, models, and tips

deeplearningexamples

Deep Learning Examples

deepmta_pytorch

Official implementation of deep-multi-trajectory-based single object tracking (IEEE T-CSVT 2021).

deepsparse

Neural network inference engine that delivers GPU-class performance for sparsified models on CPUs

deepul

dnn-based_source_separation

A PyTorch implementation of DNN-based source separation.

dnn-doa

doa-release

A Direction-of-Arrival estimation code repo accompanying our research paper.

drn

Dilated Residual Networks

dual-path-rnn-pytorch

Dual-path RNN: efficient long sequence modeling for time-domain single-channel speech separation implemented by Pytorch

flowpm

Particle Mesh simulation in TensorFlow

ganomaly

GANomaly: Semi-Supervised Anomaly Detection via Adversarial Training

gans-in-action

Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks

gaussian-processes-regression-tutorial

An Intuitive Tutorial to Gaussian Processes Regression

gccphat

git_intro

Trying out git and learning how to use it.

gmm

Variational Inference in Gaussian Mixture Model

good-papers

I try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my notes on some good papers

gp-vae

TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155

graph-adversarial-learning

A curated collection of adversarial attack and defense on graph data.

graph-neural-network-papers

Curated Lists for graph neural network, graph convolutional network, graph attention network, etc.