PyTorch implementation for " Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference" (https://arxiv.org/abs/1810.02555).
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Updated
Dec 29, 2018 - Python
PyTorch implementation for " Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference" (https://arxiv.org/abs/1810.02555).
Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features
AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
AISTATS 2019: Lovász Convolutional Networks
DPE code - Code used in "Optimal Algorithms for Multiplayer Multi-Armed Bandits" (AISTATS 2020)
Spectral Tensor Train Parameterization of Deep Learning Layers
Code for our AISTATS '22 paper: Improving Attribution Methods by Learning Submodular Functions.
A near-optimal exact sampler for discrete probability distributions
For deep RL and the future of AI.
Training Implicit Generative Models via an Invariant statistical loss (ISL)
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