sungjae-cho

sungjae-cho's Stars

• google-research/tuning_playbook

  A playbook for systematically maximizing the performance of deep learning models.

  26.6k286412.2k

• soulmachine/machine-learning-cheat-sheet

  Classical equations and diagrams in machine learning

  Language:TeX7.2k383151.2k

• asoplata/open-computational-neuroscience-resources

  A publicly-editable collection of open computational neuroscience resources

  55529883

• greenelab/lab-website-template

  An easy-to-use, flexible website template for labs.

  Language:HTML3369142300

• amoshydra/draw

  Web canvas that support pen pressure

  Language:JavaScript2929438

• locuslab/icnn

  Input Convex Neural Networks

  Language:Python27419851

• keonlee9420/Parallel-Tacotron2

  PyTorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling

  Language:Python189131944

• ConstantPark/DL_Compiler

  Study Group of Deep Learning Compiler

  14916016

• GirkovArpa/calligrapher-ai

  Handwriting Synthesis with RNNs ✍🏻

  Language:CSS1384017

• CalciferZh/AMCParser

  Parse and visualize asf/amc files from CMU MoCap dataset.

  Language:Python1355427

• snowkylin/rnn-handwriting-generation

  Handwriting generation by RNN with TensorFlow, based on "Generating Sequences With Recurrent Neural Networks" by Alex Graves

  Language:Python1047638

• chennnnnyize-zz/Optimal-Control-via-Neural-Networks

  Code repo for ICLR paper: Optimal Control Via Neural Networks: A Convex Approach

  Language:Python7510231

• KordingLab/KordingLab.github.io

  Jekyll page for Kording lab webpage

  Language:HTML661132149

• shlizee/NeuroAI

  NeuroAI-UW seminar, a regular weekly seminar for the UW community, organized by NeuroAI Shlizerman Lab.

  50714

• lancopku/AdaNorm

  Code for "Understanding and Improving Layer Normalization"

  Language:Python44730

• edwin-de-jong/incremental-sequence-learning

  Implementation of the Incremental Sequence Learning algorithms described in the Incremental Sequence Learning article

  Language:Python41116

• alewarne/Layerwise-Relevance-Propagation-for-LSTMs

  Tensorflow 2.1 implementation of LRP for LSTMs

  Language:Python376912

• fabridamicelli/echoes

  Machine Learning with Echo State Networks, a scikit-learn compatible package.

  Language:Python36418

• AliLotfi92/SNNLSTM

  Implementation of Long Short Term Spiking NN

  Language:Python34215

• EN10/KerasMNIST

  Keras MNIST for Handwriting Detection

  Language:Python254214

• BiDAlab/DeepSignDB

  24527

• cjspoerer/rcnn-sat

  Recurrent convolutional neural networks for object recognition

  Language:Python17015

• fmarcinek/LICNN

  Lateral Inhibition-Inspired Convolutional Neural Network for Visual Attention and Saliency Detection

  Language:Python13211

• jeshraghian/snn-tha

  Threshold annealing in binarized spiking neural networks

  Language:Python13201

• gyyang/KimYang2017_Cell

  Language:Python3302

• AllenInstitute/bmtk_workshop_2022

  Language:Jupyter Notebook2402

• uygarsumbul/spines

  Language:Matlab21

• xjwanglab/KimYang2017_Cell

  Language:Python21

• BiDAlab/eBioDigitDB

  1101

• kbkreddy/LSTM_variable_lenght_input_sequence

  Using keras library for applying LSTM on variable length input sequence

  Language:Python1