Jae Hyun Lim

caffe-googlenet-bn. re-implementation of googlenet batch normalization

pytorch-geometric-gan. Code accompanying the paper "Geometric GAN"

torch-inception-resnet-v2. The inception-resnet-v2 models re-trained from scratch via torch

lasagne-googlenet. Implementation of GoogLeNet with lasagne and theano

ndsb. Kaggle NDSB competition with deep learning

ddo. Official codebase for "Score-based Diffusion Models in Function Space"

pytorch-ardae-vae. AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation

python-okcoin-fix. python-okcoin-fix

lasagne-vae. re-implementation of variational auto encoder with Lasagne

pytorch-ardae-rl. AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation

intro-to-generative-models. An Introduction to Generative Modeling with Flow-Based and Diffusion-Based Models

lasagne-ram. re-implementation of Recurrent Models of Visual Attention in Lasagne (Theano)

objrcg. A package of useful functions/layers used in torch-based object-recognition

pytorch-generative-multisensory-network. Generative Multisensory Network for Neural Multisensory Scene Inference

caffe-posenet-googlenet. caffe-posenet-googlenet

multisensory-embodied-3D-scene-environment. Multisensory Embodied 3D Scene Environment

caffe. Caffe: a fast open framework for deep learning.

MAML-Pytorch. PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)

arxiv-latex-cleaner. arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv

BDMC. PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo

gym. A toolkit for developing and comparing reinforcement learning algorithms.

caffe-googlenet-bn-experiment. re-implementation of googlenet batch normalization

meta-learning-lstm. This repo contains the source code accompanying a scientific paper with the same name.

caffe-dev. customized caffe-dev

fb.resnet.torch. Torch implementation of ResNet from http://arxiv.org/abs/1512.03385 and training scripts

nms. Torch/Lua wrapper for gpu implementation of non-maximum suppression

maml_rl. Code for RL experiments in "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"