shubhampachori12110095 Goto Github PK
Name: Shubham Pachori
Type: User
Bio: Learning to extract signal from noise.
Location: Somewhere in India
Name: Shubham Pachori
Type: User
Bio: Learning to extract signal from noise.
Location: Somewhere in India
Source code for the dissertation: "Multi-Pass Deep Q-Networks for Reinforcement Learning with Parameterised Action Spaces"
A fast and differentiable model predictive control (MPC) solver for PyTorch.
New mplfinance package (replacement for mpl-finance).
自然语言处理相关实验实现 some experiment of natural language processing, Like text classification, named entity recognition, pos-tags, segment, key words extractor, auto summarize etc.
Official PyTorch implementation of Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation (ICLR 2019)
Implementation of Inference Attention Neural Networks for Reading Comprehension
A recommender systems development and evaluation package by Mendeley
Run MapReduce jobs on Hadoop or Amazon Web Services
PyTorch implementation of Mixed-Scale Dense Convolutional Neural Network (MS-D Net) for Image Analysis
Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight
Python implementation of (linear) Marginalized Stacked Denoising Autoencoder (mSDA), as well as dense Cohort of Terms (dCoT). Based on Matlab code by Minmin Chen
This is our PyTorch implementation of Multi-level Scene Description Network (MSDN) proposed in our ICCV 2017 paper.
Multi-Scale Dense Convolutional Networks for Efficient Prediction
ICLR 2018 reproducibility challenge - Multi-Scale Dense Convolutional Networks for Efficient Prediction
Depth Map Super-Resolution by Deep Multi-Scale Guidance, ECCV16
Machine Comprehension train on MSMARCO with S-NET extraction modification
Simple Python 3 morphological stemming framework
Multi-Task Deep Neural Networks for Natural Language Understanding
Information extraction to build a Knowledge Graph
MT5 compatible technical indicator functions in Python
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks
Using Caffe and python to reproduce the results of MTCNN on FDDB dataset.
Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Neural Networks
A modern LaTeX Beamer theme
Multi-task Self-supervised Object Detection via Recycling of Bounding Box Annotations (CVPR, 2019)
Code release for "Learning Multiple Tasks with Multilinear Relationship Networks" (NIPS 2017)
A simple api for google translate
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.