HUJI Deep Learning Group

HUJI Deep Learning Group's repositories

A framework based on Tensorflow for running variational Monte-Carlo simulations of quantum many-body systems.

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Experiments from the article "Tensorial Mixture Models"

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The SimNets Architecture's Implementation in Caffe

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SimNets implementation in TensorFlow

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Experiments from the paper "Inductive Bias of Deep Convolutional Networks through Pooling Geometry"

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Source code for https://arxiv.org/abs/1710.09431 - On the Long-Term Memory of Deep Recurrent Networks.

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Reference implementation for Deep Unsupervised Learning using Nonequilibrium Thermodynamics

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Experiments for the paper "On the Expressive Power of Overlapping Architectures of Deep Learning"

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Modification of original implementation, for SPN MNIST missing data experiments

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Official implementation of the experiments in the "Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks" paper.

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Efficient implementation of Generative Stochastic Networks

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GPU Optimization and Memory Abstraction Framework

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Machine learning algorithms for many-body quantum systems

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Adaptation of SPN parameter learning by Zhao et al. to support classification under missing data setting.

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A TensorFlow implementation of DeepMind's WaveNet paper

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