Jueon Park's Projects
Implementation of abstractive summarization using LSTM in the encoder-decoder architecture with local attention.
adversarial text implemented in TensorFlow 2
Complete deep learning project developed in Full Stack Deep Learning, Spring 2021
Source of the FSDL 2022 labs, which are at https://github.com/full-stack-deep-learning/fsdl-text-recognizer-2022-labs
Complete deep learning project developed in Full Stack Deep Learning, 2022 edition. Generated automatically from https://github.com/full-stack-deep-learning/fsdl-text-recognizer-2022
breakdowns XLA HLO based on its metadata
Config files for my GitHub profile.
tf 2.0 implementation of Listen, attend and spell
practice for MLIR
A fork from https://github.com/hexiangnan/neural_collaborative_filtering. Uses tf.keras instead of plain keras.
NDPX Configuration for the simulator
experiment on ndpx kernels
TensorFlow Neural Machine Translation Tutorial - with TF2 support
Simple OpenCL examples for exploiting GPU computing
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A Fast and Extensible DRAM Simulator, with built-in support for modeling many different DRAM technologies including DDRx, LPDDRx, GDDRx, WIOx, HBMx, and various academic proposals. Described in the IEEE CAL 2015 paper by Kim et al. at http://users.ece.cmu.edu/~omutlu/pub/ramulator_dram_simulator-ieee-cal15.pdf
A fast and flexible simulation infrastructure for exploring general-purpose processing-in-memory (PIM) architectures. Ramulator-PIM combines a widely-used simulator for out-of-order and in-order processors (ZSim) with Ramulator, a DRAM simulator with memory models for DDRx, LPDDRx, GDDRx, WIOx, HBMx, and HMCx. Ramulator is described in the IEEE CAL 2015 paper by Kim et al. at https://people.inf.ethz.ch/omutlu/pub/ramulator_dram_simulator-ieee-cal15.pdf Ramulator-PIM is used in the DAC 2019 paper by Singh et al. at https://people.inf.ethz.ch/omutlu/pub/NAPEL-near-memory-computing-performance-prediction-via-ML_dac19.pdf
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End-to-end speech recognition using RNN Transducers in Tensorflow 2.0
Split-Complex Neural Network
High-acc(>0.7) model(ResNet, ResNeXt, DenseNet, SENet, SE-ResNeXt) on TensorFlow.
TF2 implementation of DLRM (inherited and modified from openrec's initial implementation)
TF2 implementation of Deep Learning Recommendation Model
Add support for TF2
XLNet: Generalized Autoregressive Pretraining for Language Understanding