locussam Goto Github PK

followers: 6.0 following: 125.0 repos: 687.0 gists: 1.0

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locussam's Projects

pbrt-v3

Source code for pbrt, the renderer described in the third edition of "Physically Based Rendering: From Theory To Implementation", by Matt Pharr, Wenzel Jakob, and Greg Humphreys.

pelee

Pelee: A Real-Time Object Detection System on Mobile Devices

pennylane

PennyLane is a cross-platform Python library for quantum machine learning, automatic differentiation, and optimization of hybrid quantum-classical computations

perceptualsimilarity

Learned Perceptual Image Patch Similarity (LPIPS) metric. In CVPR, 2018.

pggan-pytorch

:fire::fire: PyTorch implementation of "Progressive growing of GANs (PGGAN)" :fire::fire:

phd-thesis

Open access to the experiments of my PhD thesis

pix2pix-tensorflow

Tensorflow port of Image-to-Image Translation with Conditional Adversarial Nets https://phillipi.github.io/pix2pix/

pix2pixhd

Synthesizing and manipulating 2048x1024 images with conditional GANs

planc

Distributed NMF Library

pmgd

Persistent Memory Graph Database

pmtk3

Probabilistic Modeling Toolkit for Matlab/Octave.

pointsetgeneration

Code for ``A Point Set Generation Network for 3D Object Reconstruction from a Single Image''

polar

C and MATLAB implementation for Polar encoding and decoding

pose-regression

Source code of paper "Human Pose Regression by Combining Indirect Part Detection and Contextual Information."

pp4fpgas

Parallel Programming for FPGAs -- An open-source high-level synthesis book

prepare-faces-zyf

prepare faces for face recognition training

privacy

Library for training machine learning models with privacy for training data

prml

Pattern recognition and machine learning toolbox

prml-1

PRML algorithms implemented in Python

prml-2

Some IPython notebooks based on Bishop's "Pattern Recognition and Machine Learning" book

prnet

The source code of 'Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network'.

probabilistic-programming-and-bayesian-methods-for-hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)