Petar Veličković (PetarV-)

PetarV-

Geek Repo

Company:Google DeepMind / University of Cambridge

Location:Cambridge, UK

Home Page:petar-v.com

Twitter:@PetarV_93

Github PK Tool:Github PK Tool


Organizations
grlearning
grlplus
mgcsweek
mila-iqia
RLGM
Team-Echo

Petar Veličković's repositories

GAT

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

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TikZ

Complete collection of my PGF/TikZ figures.

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Algorithms

Several algorithms and data structures implemented in C++ by me (credited to others where necessary).

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DGI

Deep Graph Infomax (https://arxiv.org/abs/1809.10341)

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facejack

your face has been hijacked

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muxstep

An open-source C++ multiplex HMM library for making inferences on multiple data types

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X-CNN

Cross-modal convolutional neural networks

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deep-lossy-fun

Accompanying demos for my TCES talk on loss function engineering

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deepmersion

own your surroundings

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gp

Simple C++ library for Gaussian process regression

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HashCode2017

HC2017 Qualification Round: Team МЕТАШСА (Ranked 53rd)

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pytorch-Deep-Learning

Deep Learning (with PyTorch)

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Curriculum-Vitae

The latest version of my CV (with matching cover letter), powered by LaTeX and TikZ.

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awesome-tikz

A curated list of awesome TikZ documentations, libraries and resources

a-trip-down-lstm-lane

Textual generation using character LSTMs

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advent-of-kotlin

My solutions to Advent of Code 2019 challenges, written in Kotlin.

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graph_nets

Build Graph Nets in Tensorflow

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HashCode2017Finals

HC2017 Finals: Team МЕТАШСА (Ranked 5th)

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n-hance-pls

Neural networks make your smartphone videos better... after you've filmed them

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rdkit_containers

Containers for building and working with the RDKit

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thesis

A LaTeX document class that conforms to the Computer Laboratory's PhD thesis formatting guidelines.

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HashCode2018

HC2018 Qualification Round: Team МЕТАШСА

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advent-of-perl

My solutions to Advent of Code 2017 challenges, written in Perl.

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gnn-lspe

Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations)

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home-platform

HoME: a Household Multimodal Environment is a platform for artificial agents to learn from vision, audio, semantics, physics, and interaction with objects and other agents, all within a realistic context.

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pandoc_resume

The Markdown Resume

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petarv-.github.io

Personal website (developed by David Davidović)

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