Lim Swee Kiat

lucent. Lucid library adapted for PyTorch

attention-primer. A demonstration of the attention mechanism with some toy experiments and explanations.

boundary-attack. Implementation of the Boundary Attack algorithm as described in Brendel, Wieland, Jonas Rauber, and Matthias Bethge. "Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models." arXiv preprint arXiv:1712.04248 (2017).

deep-learning-book-notes. Notes on Deep Learning textbook by Ian Goodfellow, Yoshua Bengio and Aaron Courville

redditle. Vue

pysc2-RLagents. Notes and scripts for SC2LE released by DeepMind and Blizzard, more details [here](https://github.com/deepmind/pysc2).

keras-aae. Implementation of Adversarial Autoencoder in Keras

cond-shift-neurons. Implementation of Conditionally Shifted Neurons by Munkhdalai et al. (https://arxiv.org/pdf/1712.09926.pdf)

lucent-notebooks. Colab/Jupyter notebooks based on Lucent.

compute-your-own-neuralhash. Simple demo to compute your own NeuralHash on-device.

apple-neuralhash-attack. Demonstrates iterative FGSM on Apple's NeuralHash model.

maml-reptile. Implementation of MAML and Reptile algorithms with a JS demo on the sine regression toy experiment

doping. Code for DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN

few-shot-without-forgetting-tensorflow. Tensorflow implementation of Dynamic Few-Shot Visual Learning without Forgetting by Gidaris & Komodakis

tensorflow-dagmm. Tensorflow reproduction of DAGMM

pocoloco. JavaScript

dollar-street-images. Link to downloadable images from Gapminder's Dollar Street dataset

cs236g-fonts. Final project for CS236G Winter 2021

adversarialautoencoder. Replicates Adversarial Autoencoder architecture from [Makhzani, Alireza, et al. "Adversarial autoencoders." arXiv preprint arXiv:1511.05644 (2015)](https://arxiv.org/abs/1511.05644). The code is adapted from Naresh's implementation [here](https://github.com/Naresh1318/Adversarial_Autoencoder).

project-asimov. A guide to pressing ethical matters in artificial intelligence technologies.

patterns. Work on CPPNs, inspired by @hardmaru

twigge. Vue

sauces. The easiest way to distribute and download datasets! Used by authors and competition organizers in NeurIPS, CVPR, ACL.

viper. Build your frontend with Python