Joey Litalien (joeylitalien)

joeylitalien

Geek Repo

Company:McGill University

Location:Montreal, Canada

Home Page:joeylitalien.github.io

Twitter:@JoeyLitalien

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Joey Litalien's repositories

noise2noise-pytorch

PyTorch Implementation of Noise2Noise (Lehtinen et al., 2018)

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celeba-gan-pytorch

Generative Adversarial Networks in PyTorch

interactive-viewer

An online test suite for rendering research, based on Disney Research's interactive viewer

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drmlt

Delayed Rejection Metropolis Light Transport (Rioux-Lavoie et al., 2020)

l2hmc

ICLR 2018 Reproducibility Challenge: Generalizing Hamiltonian Monte Carlo with Neural Networks

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drmlt-mitsuba

Delayed Rejection Metropolis Light Transport (PSSMLT & MMLT Applications)

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drmlt-dpt

Delayed Rejection Metropolis Light Transport (H2MC Application)

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mlt

Metropolis Light Transport (Reading Group)

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joeylitalien.github.io

Personal website

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mitsuba2

Mitsuba 2: A Retargetable Forward and Inverse Renderer

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rayone

A comprehensive global illumination renderer

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2d-fluids

2D Fluid Simulation with Different Numerical Solvers for the Poisson Problem

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beer-manager

A simple tool to manage beers on display for small bars and pubs

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COMP-310

Operating Systems

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comp-551-a4

COMP 551: Applied Machine Learning ā€” Project #4

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CovarianceTracing

Headers, tests, and examples for Covariance Tracing

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ecseX46-submission

Submission script for ECSE X46 / COMP 598 Realistic/Advanced Image Synthesis

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fall-2019

ECSE 446/546: Realistic/Advanced Image Synthesis

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fed-sim

Federated Simulation for Medical Imaging (MICCAI2020)

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ift6135-a1

Assignment 1: Multilayer Perceptrons

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ift6135-a2

CNNs, Regularization and Normalization

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kaolin-wisp

NVIDIA Kaolin Wisp is a PyTorch library powered by NVIDIA Kaolin Core to work with neural fields (including NeRFs, NGLOD, instant-ngp and VQAD).

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lab-website

Lab website for the graphics group at McGill University

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mitsuba

Mitsuba renderer main repository

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mitsuba-data

Data files for Mitsuba 2

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nerf-pytorch

A PyTorch implementation of NeRF (Neural Radiance Fields) that reproduces the results.

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NeuS

Code release for NeuS

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pbrt-v2

Source code for the version of pbrt described in the second edition of "Physically Based Rendering"

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pbrt-v3-1

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.

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pytorch-cpp

Pytorch C++ Library

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