Name: Prince
Type: User
Company: Carnegie Mellon University
Bio: Doing AI research, including but not limited to, machine learning, statistical learning theory, variational inference
Location: California, Santa Barbara
Blog: https://kingofspace0wzz.github.io
Prince's Projects
Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning
Implements pytorch code for the Accelerated SGD algorithm.
Code for the paper, Neural Network Attributions: A Causal Perspective (ICML 2019).
Code for "Autoregressive flow-based causal discovery and inference" - ICML INNF workshop, 2020
Algorithms and Data Structures in Python
180+ Algorithm & Data Structure Problems using C++
A curated list of awesome Self-Supervised methods
Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
BERT score for language generation
Pytorch implementation of Block Neural Autoregressive Flow
A PyTorch implementation of the NIPS 2017 paper "Dynamic Routing Between Capsules".
Code for paper Causal Confusion in Imitation Learning
Compare GAN code.
Algorithms and Computations in Computational Geometry
:mortar_board: Path to a free self-taught education in Computer Science!
Implementations of ideas from recent papers
Code and report of project "Controlable-Factorized VAE"
A technical report on convolution arithmetic in the context of deep learning
Image cognition using Convolutional Restricted Boltzmann Machines
Tutorials for Fall 2018
Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.