jaks19 Goto Github PK
Name: Adarsh K. Jeewajee
Type: User
Company: Stanford
Bio: First-year CS PhD student at Stanford University
Twitter: AdarshJeewajee
Location: Stanford University
Name: Adarsh K. Jeewajee
Type: User
Company: Stanford
Bio: First-year CS PhD student at Stanford University
Twitter: AdarshJeewajee
Location: Stanford University
18.06 course at MIT in Spring 2017
Software parses musical pieces in abc notation (.abc files) and plays them
Find and fix bugs in natural language machine learning models using adaptive testing.
An augmented reality that places cute running animals all around your room. Gotta photograph 'em all!
BipedalWalker-V2 on varying terrains, with morphology adaptation
An ongoing Web Application project which allows a player to play Checkers against the computer. Rules and graphics have been properly implemented and the game works with limited functionality. Final update on user input manipulation up and coming. (Right now a user can move by requesting any legal move but now user will be allowed to click on a checker and move it instead).
pytorch Convolutional Networks for Sentence Classification - http://www.aclweb.org/anthology/D14-1181
A very simple implementation of cyclegan, which is based on pytorch.
deeplearning.ai , By Andrew Ng, All slide and notebook + code and some material.
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://nervanasystems.github.io/distiller
Undirected graphical models are compact representations of joint probability distributions over random variables. To solve inference tasks of interest, graphical models of arbitrary topology can be trained using empirical risk minimization. However, to solve inference tasks that were not seen during training, these models (EGMs) often need to be re-trained. Instead, we propose an inference-agnostic adversarial training framework which produces an infinitely-large ensemble of graphical models (AGMs). The ensemble is optimized to generate data within the GAN framework, and inference is performed using a finite subset of these models. AGMs perform comparably with EGMs on inference tasks that the latter were specifically optimized for. Most importantly, AGMs show significantly better generalization to unseen inference tasks compared to EGMs, as well as deep neural architectures like GibbsNet and VAEAC which allow arbitrary conditioning. Finally, AGMs allow fast data sampling, competitive with Gibbs sampling from EGMs.
Optimizing the morphology of robotic fingers for increased object grasping accuracy on adversarially-shaped objects
Web application allows English speakers learning Spanish to practice their skills by giving the correct English translation of Spanish words.
Hosts a Server to play command-line Multiplayer Minesweeper. Objective of the game: Stay alive for the longest possible time.
Max entropy and RNN models used to detect GENE NAMES in biological academic literature
Using LSTM and CNN trained on the stack exchange Ubuntu dataset for the question similarity task on the Android dataset, using transfer learning for domain adaptation.
Repo of code used in my 6.UAP Undergraduate EECS Thesis at MIT
Parallel WSG-32 Gripper Simulation with a GUI wrapper and a Grasping-Routine wrapper
Implementations of Machine Learning Algorithms in PyTorch
A Unity3D game where the user is a cube that has to navigate through a map full of obstacles and mazes to reach its goal and keep moving up the levels.
Scene generation from novel viewpoints - Graph element networks
A neural net model used to classify movie review sentiments using word embeddings for reviews
A URDF of a Jaco2 arm and Robotiq 2-finger gripper, and an example PyBullet environment for control
A portal for Students and Admin-alike to manage subscriptions, payments, file submission and review and aims to build community through a forum.
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.