greydanus

Sam's repositories

hamiltonian-nn

Code for our paper "Hamiltonian Neural Networks"

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scribe

Realistic Handwriting with Tensorflow

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baby-a3c

A high-performance Atari A3C agent in 180 lines of PyTorch

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crypto-rnn

Learning the Enigma with Recurrent Neural Networks

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mnist1d

A 1D analogue of the MNIST dataset for measuring spatial biases and answering Science of Deep Learning questions.

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visualize_atari

Code for our paper "Visualizing and Understanding Atari Agents" (https://goo.gl/AMAoSc)

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pythonic_ocr

A convolutional neural network implemented in pure numpy.

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excitationbp

Visualizing how deep networks make decisions

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psi0nn

A neural network quantum ground state solver

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optimize_wing

We simulate a wind tunnel, place a rectangular occlusion in it, and then use gradient descent to turn the occlusion into a wing.

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ncf

Nature's Cost Function (NCF). Finding paths of least action with gradient descent.

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greydanus.github.io

My academic blog

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structural_optimization

Coding structural optimization, from scratch, in 200 lines of Python

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studying_growth

Studying Cell Growth with Neural Cellular Automata

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mnist-gan

Generative Adversarial Networks for the MNIST dataset

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np_nets

Neural network experiments written purely in numpy

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subspace-nn

Optimizing neural networks in subspaces

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piecewise_node

Temporal abstraction for autoregressive sampling

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baselines

Simple MNIST baselines for 1) numpy backprop 2) dense nns 3) cnns 3) seq2seq

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compton

Exploring the quantum nature of light with compton scattering

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deep_thesaurus

Use a pretrained NLP model to rank thesaurus suggestions

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karpathy.github.io

my blog

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dissipative_hnns

Fork from Sosanya's GitHub of our code for "Dissipative HNNs"

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generic_heroku

A repo for hosting a generic Heroku app

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lagrangian_nns

Fork of codebase from Miles Cranmer's GitHub

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minirts

import numpy as np and enjoy

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neural-structural-optimization

Neural reparameterization improves structural optimization

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papers

Paper reviews for my work with the XAI group at Oregon State

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pderl

Code for "Proximal Distilled Evolutionary Reinforcement Learning", accepted at AAAI 2020

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pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

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