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chimera0
accelbrainbeat

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

2K 325 91
chimera0
pydbm

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

2K 325 91
accel-brain
pysummarization

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

1K 325 91
kousuke-nakano
jqmc

No description available

997 15 1
accel-brain
pyqlearning

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

983 325 91
accel-brain
accel-brain-base

accel-brain-base is a basic library of the Deep Learning for rapid development at low cost. This library makes it possible to design and implement deep learning, which must be configured as a complex system, by combining a plurality of functionally differentiated modules such as a Deep Boltzmann Machines(DBMs), an Auto-Encoder, an Encoder/Decoder based on Long Short-Term Memory(LSTM), a Convolutional Auto-Encoder(CAE), and Transformer.

584 325 91
deepqmc
deepqmc

Deep learning quantum Monte Carlo for electrons in real space

579 413 62
accel-brain
pygan

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

494 325 91
accel-brain
pycomposer

pycomposer is Python library for Algorithmic Composition or Automatic Composition based on the stochastic music theory and the Statistical machine learning problems. Especialy, this library provides apprication of the Algorithmic Composer based on Generative Adversarial Networks(GANs) and Conditional Generative Adversarial Networks(Conditional GANs).

348 325 91
nscottnichols
erroranalysis-py

Generate error bars and perform binning analysis using jackknife or bootstrap resampling. Calculate average and error in quantum Monte Carlo data (or other data) and on functions of averages (such as fluctuations, skew, and kurtosis).

337 5 1
Konjkov
casino

Python realisation of Casino (QMC) program

141 6 0
accel-brain
algo-wars

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

56 325 91
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