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Kelly Marshall's Projects

3d-llm icon 3d-llm

Code for 3D-LLM: Injecting the 3D World into Large Language Models

bds_hw2 icon bds_hw2

Code for the second assignment of Big Data Science, written by Alex Bogetc. and Kelly Marshall

big_graph icon big_graph

Course Project for Spring 2021 Big Data course

control-pcgrl icon control-pcgrl

A package for "Procedural Content Generation via Reinforcement Learning" OpenAI Gym interface.

dp_layer icon dp_layer

C++/CUDA implementation of differentiable dynamic programming layer

graphics icon graphics

TensorFlow Graphics: Differentiable Graphics Layers for TensorFlow

hybrid-genetic-algorithm icon hybrid-genetic-algorithm

Implementation of my proposed hybrid algorithm for deep reinforcement learning. Combines the gradient-based PPO algorithm with a gradient-free genetic algorithm

km3888.github.io icon km3888.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

mlsh icon mlsh

Code for the paper "Meta-Learning Shared Hierarchies"

music-analysis-project icon music-analysis-project

Repository for Spring 2019 Big Data Science term project by Kelly Marshall and Alex Bogdanowicz

oyster_hier icon oyster_hier

Implementation of Efficient Off-policy Meta-learning via Probabilistic Context Variables (PEARL)

pong icon pong

A fun side project mean to foster competitiveness amongst those playing ping pong at NYU Shanghai. Uses Pandas to load the data collectively contributed by those who logged their games on a Google Sheet. This data is then analyzed to show personal stats, one-on-one matchups, and uses an ELO system based on binomial probabilities to rank players who have played sufficient games.

rlkit icon rlkit

Collection of reinforcement learning algorithms

simclr icon simclr

PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations

torchsort icon torchsort

Fast, differentiable sorting and ranking in PyTorch

transformers icon transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

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